Journal articles on the topic 'Mobile Mapping System (MMS)'
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1
Al-Hamad, A., and N. El-Sheimy. "Smartphones Based Mobile Mapping Systems." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5 (June 5, 2014): 29–34. http://dx.doi.org/10.5194/isprsarchives-xl-5-29-2014.
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The past 20 years have witnessed an explosive growth in the demand for geo-spatial data. This demand has numerous sources and takes many forms; however, the net effect is an ever-increasing thirst for data that is more accurate, has higher density, is produced more rapidly, and is acquired less expensively. For mapping and Geographic Information Systems (GIS) projects, this has been achieved through the major development of Mobile Mapping Systems (MMS). MMS integrate various navigation and remote sensing technologies which allow mapping from moving platforms (e.g. cars, airplanes, boats, etc.) to obtain the 3D coordinates of the points of interest. Such systems obtain accuracies that are suitable for all but the most demanding mapping and engineering applications. However, this accuracy doesn't come cheaply. As a consequence of the platform and navigation and mapping technologies used, even an "inexpensive" system costs well over 200 000 USD. Today's mobile phones are getting ever more sophisticated. Phone makers are determined to reduce the gap between computers and mobile phones. Smartphones, in addition to becoming status symbols, are increasingly being equipped with extended Global Positioning System (GPS) capabilities, Micro Electro Mechanical System (MEMS) inertial sensors, extremely powerful computing power and very high resolution cameras. Using all of these components, smartphones have the potential to replace the traditional land MMS and portable GPS/GIS equipment. This paper introduces an innovative application of smartphones as a very low cost portable MMS for mapping and GIS applications.
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Wan, Rui, Yuchun Huang, Rongchang Xie, and Ping Ma. "Combined Lane Mapping Using a Mobile Mapping System." Remote Sensing 11, no. 3 (February 2, 2019): 305. http://dx.doi.org/10.3390/rs11030305.
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High-definition mapping of 3D lane lines has been widely needed for the highway documentation and intelligent navigation of autonomous systems. A mobile mapping system (MMS) captures both accurate 3D LiDAR point clouds and high-resolution images of lane markings at highway driving speeds, providing an abundant data source for combined lane mapping. This paper aims to map lanes with an MMS. The main contributions of this paper include the following: (1) an intensity correction method was introduced to eliminate the reflectivity inconsistency of road-surface LiDAR points; (2) a self-adaptive thresholding method was developed to extract lane markings from their complicated surroundings; and (3) a LiDAR-guided textural saliency analysis of MMS images was proposed to improve the robustness of lane mapping. The proposed method was tested with a dataset acquired in Wuhan, Hubei, China, which contained straight roads, curved roads, and a roundabout with various pavement markings and a complex roadside environment. The experimental results achieved a recall of 96.4%, a precision of 97.6%, and an F-score of 97.0%, demonstrating that the proposed method has strong mapping ability for various urban roads.
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Al-Hamad, A., A. Moussa, and N. El-Sheimy. "Video-based Mobile Mapping System Using Smartphones." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (November 7, 2014): 13–18. http://dx.doi.org/10.5194/isprsarchives-xl-1-13-2014.
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The last two decades have witnessed a huge growth in the demand for geo-spatial data. This demand has encouraged researchers around the world to develop new algorithms and design new mapping systems in order to obtain reliable sources for geo-spatial data. Mobile Mapping Systems (MMS) are one of the main sources for mapping and Geographic Information Systems (GIS) data. MMS integrate various remote sensing sensors, such as cameras and LiDAR, along with navigation sensors to provide the 3D coordinates of points of interest from moving platform (e.g. cars, air planes, etc.). Although MMS can provide accurate mapping solution for different GIS applications, the cost of these systems is not affordable for many users and only large scale companies and institutions can benefits from MMS systems. <br><br> The main objective of this paper is to propose a new low cost MMS with reasonable accuracy using the available sensors in smartphones and its video camera. Using the smartphone video camera, instead of capturing individual images, makes the system easier to be used by non-professional users since the system will automatically extract the highly overlapping frames out of the video without the user intervention. Results of the proposed system are presented which demonstrate the effect of the number of the used images in mapping solution. In addition, the accuracy of the mapping results obtained from capturing a video is compared to the same results obtained from using separate captured images instead of video.
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Ishikawa, Kiichiro, Jun-ichi Takiguchi, Yoshiharu Amano, Takumi Hashizume, and Takashi Fujishima. "Tunnel Cross-Section Measurement System Using a Mobile Mapping System." Journal of Robotics and Mechatronics 21, no. 2 (April 20, 2009): 193–99. http://dx.doi.org/10.20965/jrm.2009.p0193.
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This paper describes a tunnel cross-section measurement system using a mobile mapping system (MMS). The MMS features a GPS/ Dead Reckoning (DR) combined navigation system, a three-axis GPS-Gyro/ Inertial Measurement Unit (IMU), laser scanners, cameras, and the Network-based Positioning Augmentation Services (PAS). As GPS cannot be used in the tunnel, so the position estimation is done using IMU and Odometer. In this paper the result of comparison between the conventional tunnel cross-section measurement methods using 3D laser scanner and total station, and the proposed method using the MMS is described. And the examination result of the MMS's positioning accuracy that doesn't use GPS is described. The evaluation result proves that the tunnel cross-section measurement accuracy using the MMS is 7.0 mm, the MMS's measurement accuracy is not different from conventional method using a 3D laser scanner and a total station. The MMS tunnel measurement efficiency is also confirmed in this paper.
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Yu, Peidong, Mengke Wang, and Huanjian Chen. "Integration and evaluation of SLAM-based backpack mobile mapping system." E3S Web of Conferences 206 (2020): 03014. http://dx.doi.org/10.1051/e3sconf/202020603014.
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Mobile mapping is an efficient technology to acquire spatial data of the environment. As a supplement of vehicle-borne and air-borne methods, Backpack mobile mapping system (MMS) has a wide application prospect in indoor and underground space. High-precision positioning and attitude determination are the key to MMS. Usually, GNSS/INS integrated navigation system provides reliable pose information. However, in the GNSS-denied environments, there is no effective long-term positioning method. With the development of simultaneous localization and mapping (SLAM) algorithm, it provides a new solution for indoor mobile mapping. This paper develops a portable backpack mobile mapping system, which integrates multi-sensor such as LiDAR, IMU, GNSS and panoramic camera. The 3D laser SLAM algorithm is applied to the mobile mapping to realize the acquisition of geographic information data in various complex environments. The experimental results in typical indoor and outdoor scenes show that the system can achieve high-precision and efficient acquisition of 3D information, and the relative precision of point cloud is 2~4cm, which meets the requirements of scene mapping and reconstruction.
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Di Pietra, V., N. Grasso, M. Piras, and P. Dabove. "CHARACTERIZATION OF A MOBILE MAPPING SYSTEM FOR SEAMLESS NAVIGATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 227–34. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-227-2020.
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Abstract. Mobile Mapping Systems (MMS) are multi-sensor technologies based on SLAM procedure, which provides accurate 3D measurement and mapping of the environment as also trajectory estimation for autonomous navigation. The major limits of these algorithms are the navigation and mapping inconsistence over the time and the georeferencing of the products. These issues are particularly relevant for pose estimation regardless the environment like in seamless navigation. This paper is a preliminary analysis on a proposed multi-sensor platform integrated for indoor/outdoor seamless positioning system. In particular the work is devoted to analyze the performances of the MMS in term of positioning accuracy and to evaluate its improvement with the integration of GNSS and UWB technology. The results show that, if the GNSS and UWB signal are not degraded, using the correct weight to their observations in the Stencil estimation algorithm, is possible to obtain an improvement in the accuracy of the MMS navigation solution as also in the global consistency of the final point cloud. This improvement is measured in about 7 cm for planimetric coordinate and 34 cm along the elevation with respect to the use of the Stencil system alone.
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Juraj, Čerňava, Tuček Ján, Koreň Milan, and Mokroš Martin. "Estimation of diameter at breast height from mobile laser scanning data collected under a heavy forest canopy." Journal of Forest Science 63, No. 9 (September 21, 2017): 433–41. http://dx.doi.org/10.17221/28/2017-jfs.
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Mobile laser scanning (MLS) is time-efficient technology of geospatial data collection that proved its ability to provide accurate measurements in many fields. Mobile innovation of the terrestrial laser scanning has a potential to collect forest inventory data on a tree level from large plots in a short time. Valuable data, collected using mobile mapping system (MMS), becomes very difficult to process when Global Navigation Satellite System (GNSS) outages become too long. A heavy forest canopy blocking the GNSS signal and limited accessibility can make mobile mapping very difficult. This paper presents processing of data collected by MMS under a heavy forest canopy. DBH was estimated from MLS point cloud using three different methods. Root mean squared error varied between 2.65 and 5.57 cm. Our research resulted in verification of the influence of MLS coverage of tree stem on the accuracy of DBH data.
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Kerstinga, A. P., and P. Friess. "POST-MISSION QUALITY ASSURANCE PROCEDURE FOR SURVEY-GRADE MOBILE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 647–52. http://dx.doi.org/10.5194/isprs-archives-xli-b1-647-2016.
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Mobile Mapping Systems (MMS) consist of terrestrial-based moving platforms that integrate a set of imaging sensors (typically digital cameras and laser scanners) and a Position and Orientation System (POS), designed to collect data of the surrounding environment. MMS can be classified as “mapping-grade” or “survey-grade” depending on the system’s attainable accuracy. Mapping-grade MMS produce geospatial data suitable for GIS applications (e.g., asset management) while survey-grade systems should satisfy high-accuracy applications such as engineering/design projects. The delivered accuracy of an MMS is dependent on several factors such as the accuracy of the system measurements and calibration parameters. It is critical, especially for survey-grade systems, to implement a robust Quality Assurance (QA) procedure to ensure the achievement of the expected accuracy. In this paper, a new post-mission QA procedure is presented. The presented method consists of a fully-automated self-calibration process that allows for the estimation of corrections to the system calibration parameters (e.g., boresight angles and lever-arm offsets relating the lidar sensor(s) to the IMU body frame) as well as corrections to the system measurements (e.g., post-processed trajectory position and orientation, scan angles and ranges). As for the system measurements, the major challenge for MMS is related to the trajectory determination in the presence of multipath signals and GNSS outages caused by buildings, underpasses and high vegetation. In the proposed self-calibration method, trajectory position errors are properly modelled while utilizing an efficient/meaningful trajectory segmentation technique. The validity of the proposed method is demonstrated using a dataset collected under unfavorable GNSS conditions.
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Kerstinga, A. P., and P. Friess. "POST-MISSION QUALITY ASSURANCE PROCEDURE FOR SURVEY-GRADE MOBILE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 647–52. http://dx.doi.org/10.5194/isprsarchives-xli-b1-647-2016.
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Mobile Mapping Systems (MMS) consist of terrestrial-based moving platforms that integrate a set of imaging sensors (typically digital cameras and laser scanners) and a Position and Orientation System (POS), designed to collect data of the surrounding environment. MMS can be classified as “mapping-grade” or “survey-grade” depending on the system’s attainable accuracy. Mapping-grade MMS produce geospatial data suitable for GIS applications (e.g., asset management) while survey-grade systems should satisfy high-accuracy applications such as engineering/design projects. The delivered accuracy of an MMS is dependent on several factors such as the accuracy of the system measurements and calibration parameters. It is critical, especially for survey-grade systems, to implement a robust Quality Assurance (QA) procedure to ensure the achievement of the expected accuracy. In this paper, a new post-mission QA procedure is presented. The presented method consists of a fully-automated self-calibration process that allows for the estimation of corrections to the system calibration parameters (e.g., boresight angles and lever-arm offsets relating the lidar sensor(s) to the IMU body frame) as well as corrections to the system measurements (e.g., post-processed trajectory position and orientation, scan angles and ranges). As for the system measurements, the major challenge for MMS is related to the trajectory determination in the presence of multipath signals and GNSS outages caused by buildings, underpasses and high vegetation. In the proposed self-calibration method, trajectory position errors are properly modelled while utilizing an efficient/meaningful trajectory segmentation technique. The validity of the proposed method is demonstrated using a dataset collected under unfavorable GNSS conditions.
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Tsai, G. J., K. W. Chiang, C. H. Chu, Y. L. Chen, N. El-Sheimy, and A. Habib. "THE PERFORMANCE ANALYSIS OF AN INDOOR MOBILE MAPPING SYSTEM WITH RGB-D SENSOR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W4 (August 26, 2015): 183–88. http://dx.doi.org/10.5194/isprsarchives-xl-1-w4-183-2015.
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Over the years, Mobile Mapping Systems (MMSs) have been widely applied to urban mapping, path management and monitoring and cyber city, etc. The key concept of mobile mapping is based on positioning technology and photogrammetry. In order to achieve the integration, multi-sensor integrated mapping technology has clearly established. In recent years, the robotic technology has been rapidly developed. The other mapping technology that is on the basis of low-cost sensor has generally used in robotic system, it is known as the Simultaneous Localization and Mapping (SLAM). The objective of this study is developed a prototype of indoor MMS for mobile mapping applications, especially to reduce the costs and enhance the efficiency of data collection and validation of direct georeferenced (DG) performance. The proposed indoor MMS is composed of a tactical grade Inertial Measurement Unit (IMU), the Kinect RGB-D sensor and light detection, ranging (LIDAR) and robot. In summary, this paper designs the payload for indoor MMS to generate the floor plan. In first session, it concentrates on comparing the different positioning algorithms in the indoor environment. Next, the indoor plans are generated by two sensors, Kinect RGB-D sensor LIDAR on robot. Moreover, the generated floor plan will compare with the known plan for both validation and verification.
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Al-Durgham, Kaleel, Derek D. Lichti, Eunju Kwak, and Ryan Dixon. "Automated Accuracy Assessment of a Mobile Mapping System with Lightweight Laser Scanning and MEMS Sensors." Applied Sciences 11, no. 3 (January 23, 2021): 1007. http://dx.doi.org/10.3390/app11031007.
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The accuracy assessment of mobile mapping system (MMS) outputs is usually reliant on manual labor to inspect the quality of a vast amount of collected geospatial data. This paper presents an automated framework for the accuracy assessment and quality inspection of point cloud data collected by MMSs operating with lightweight laser scanners and consumer-grade microelectromechanical systems (MEMS) sensors. A new, large-scale test facility has been established in a challenging navigation environment (downtown area) to support the analyses conducted in this research work. MMS point cloud data are divided into short time slices for comparison with the higher-accuracy, terrestrial laser scanner (TLS) point cloud of the test facility. MMS data quality is quantified by the results of registering the point cloud of each slice with the TLS datasets. Experiments on multiple land vehicle MMS point cloud datasets using a lightweight laser scanner and three different MEMS devices are presented to demonstrate the effectiveness of the proposed method. The mean accuracy of a consumer grade MEMS (<$100) was found to be 1.13 ± 0.47 m. The mean accuracy of two commercial MEMS (>$100) was in the range of 0.48 ± 0.23 m to 0.85 ± 0.52 m. The method presented here in can be straightforwardly implemented and adopted for the accuracy assessment of other MMSs types such as unmanned aerial vehicles (UAV)s.
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Manish, Raja, Yi-Chun Lin, Radhika Ravi, Seyyed Meghdad Hasheminasab, Tian Zhou, and Ayman Habib. "Development of a Miniaturized Mobile Mapping System for In-Row, Under-Canopy Phenotyping." Remote Sensing 13, no. 2 (January 14, 2021): 276. http://dx.doi.org/10.3390/rs13020276.
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This paper focuses on the development of a miniaturized mobile mapping platform with advantages over current agricultural phenotyping systems in terms of acquiring data that facilitate under-canopy plant trait extraction. The system is based on an unmanned ground vehicle (UGV) for in-row, under-canopy data acquisition to deliver accurately georeferenced 2D and 3D products. The paper addresses three main aspects pertaining to the UGV development: (a) architecture of the UGV mobile mapping system (MMS), (b) quality assessment of acquired data in terms of georeferencing information as well as derived 3D point cloud, and (c) ability to derive phenotypic plant traits using data acquired by the UGV MMS. The experimental results from this study demonstrate the ability of the UGV MMS to acquire dense and accurate data over agricultural fields that would facilitate highly accurate plant phenotyping (better than above-canopy platforms such as unmanned aerial systems and high-clearance tractors). Plant centers and plant count with an accuracy in the 90% range have been achieved.
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Khoramshahi, Ehsan, Mariana Campos, Antonio Tommaselli, Niko Vilijanen, Teemu Mielonen, Harri Kaartinen, Antero Kukko, and Eija Honkavaara. "Accurate Calibration Scheme for a Multi-Camera Mobile Mapping System." Remote Sensing 11, no. 23 (November 25, 2019): 2778. http://dx.doi.org/10.3390/rs11232778.
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Mobile mapping systems (MMS) are increasingly used for many photogrammetric and computer vision applications, especially encouraged by the fast and accurate geospatial data generation. The accuracy of point position in an MMS is mainly dependent on the quality of calibration, accuracy of sensor synchronization, accuracy of georeferencing and stability of geometric configuration of space intersections. In this study, we focus on multi-camera calibration (interior and relative orientation parameter estimation) and MMS calibration (mounting parameter estimation). The objective of this study was to develop a practical scheme for rigorous and accurate system calibration of a photogrammetric mapping station equipped with a multi-projective camera (MPC) and a global navigation satellite system (GNSS) and inertial measurement unit (IMU) for direct georeferencing. The proposed technique is comprised of two steps. Firstly, interior orientation parameters of each individual camera in an MPC and the relative orientation parameters of each cameras of the MPC with respect to the first camera are estimated. In the second step the offset and misalignment between MPC and GNSS/IMU are estimated. The global accuracy of the proposed method was assessed using independent check points. A correspondence map for a panorama is introduced that provides metric information. Our results highlight that the proposed calibration scheme reaches centimeter-level global accuracy for 3D point positioning. This level of global accuracy demonstrates the feasibility of the proposed technique and has the potential to fit accurate mapping purposes.
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Maset, E., S. Cucchiaro, F. Cazorzi, F. Crosilla, A. Fusiello, and A. Beinat. "INVESTIGATING THE PERFORMANCE OF A HANDHELD MOBILE MAPPING SYSTEM IN DIFFERENT OUTDOOR SCENARIOS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2021 (June 28, 2021): 103–9. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2021-103-2021.
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Abstract. In recent years, portable Mobile Mapping Systems (MMSs) are emerging as valuable survey instruments for fast and efficient mapping of both internal and external environments. The aim of this work is to assess the performance of a commercial handheld MMS, Gexcel HERON Lite, in two different outdoor applications. The first is the mapping of a large building, which represents a standard use-case scenario of this technology. Through the second case study, that consists in the survey of a torrent reach, we investigate instead the applicability of the handheld MMS for natural environment monitoring, a field in which portable systems are not yet widely employed. Quantitative and qualitative assessment is presented, comparing the point clouds obtained from the HERON Lite system against reference models provided by traditional techniques (i.e., Terrestrial Laser Scanning and Photogrammetry).
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Tachi, T., Y. Wang, R. Abe, T. Kato, N. Maebashi, and N. Kishimoto. "DEVELOPMENT OF VERSATILE MOBILE MAPPING SYSTEM ON A SMALL SCALE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 271–75. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-271-2020.
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Abstract. Mobile mapping technology is an effective method to collect geospatial data with high point density and accuracy. It is mainly used for asset inventory and map generation, as well as road maintenance (detecting road cracks and ruts, and measuring flatness). Equipment of former mobile mapping systems (MMS) is large in size and usually installed (hard-mounted) onto dedicated vehicle. Cost-effectiveness and flexibility of MMS have not been regarded as important until Leica Pegasus series, a much smaller system with integrated and configurable components, come out. In this paper, we show you how we realize a versatile MMS with a Pegasus II loaded on a remodelled Japanese light vehicle (small size and less than a cubic capacity of 660 cc). Besides Pegasus II and data-processing PC, we equip this system with a small crane to bring the sensor onto a different platform, an electric cart to survey narrow roads or pedestrian walkway, and a boat attachment so that the sensor can be fixed on a boat. Thus, one Pegasus II can collect data from various platforms. This paper also discusses the precision and accuracy of the Pegasus II working on various platforms. When mounted on a light vehicle, we verified the accuracy of the difference with GCP and evaluated the accuracy of the road maintenance (detecting road cracks and ruts, and measuring flatness). When mounted on an electric cart, we verified the accuracy of the difference with GCP on a pedestrian road and generated road hazard map as a data utilization. When mounted on a boat, we verified the accuracy of the difference with GCP on a dam slope and created slope shading map of landslide area as a data utilization. It turns out that Pegasus II can totally achieve to required surveying-grade.
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Maboudi, M., D. Bánhidi, and M. Gerke. "INVESTIGATION OF GEOMETRIC PERFORMANCE OF AN INDOOR MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 637–42. http://dx.doi.org/10.5194/isprs-archives-xlii-2-637-2018.
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Up-to-date and reliable 3D information of indoor environments is a prerequisite for many location- based services. One possibility to capture the necessary 3D data is to make use of Mobile Mapping Systems (MMSs) which rely for instance on SLAM (simultaneous localization and mapping). In most indoor environments, MMSs are by far faster than classic static systems. Moreover, they might deliver the point clouds with higher degree of completeness. In this paper, the geometric quality of point clouds of a state-of-the-art MMS (Viametris iMS3D) is investigated. In order to quantify the quality of iMS3D MMS, four different evaluation strategies namely cloud to cloud, point to plane, target to target and model based evaluation are employed. We conclude that the measurement accuracies are better than 1&thinsp;cm and the precision of the point clouds are better than 3&thinsp;cm in our experiments. For indoor mapping applications with few centimeters accuracy, the system offers a very fast solution. Moreover, as a nature of the current SLAM-based approaches, trajectory loop should be closed, but in some practical situations, closing the local trajectory loop might not be always possible. Our observation reveals that performing continuous repeated scanning could decrease the destructive effect of local unclosed loops.
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Peng, Cheng-Wei, Chen-Chien Hsu, and Wei-Yen Wang. "Cost Effective Mobile Mapping System for Color Point Cloud Reconstruction." Sensors 20, no. 22 (November 16, 2020): 6536. http://dx.doi.org/10.3390/s20226536.
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Survey-grade Lidar brands have commercialized Lidar-based mobile mapping systems (MMSs) for several years now. With this high-end equipment, the high-level accuracy quality of point clouds can be ensured, but unfortunately, their high cost has prevented practical implementation in autonomous driving from being affordable. As an attempt to solve this problem, we present a cost-effective MMS to generate an accurate 3D color point cloud for autonomous vehicles. Among the major processes for color point cloud reconstruction, we first synchronize the timestamps of each sensor. The calibration process between camera and Lidar is developed to obtain the translation and rotation matrices, based on which color attributes can be composed into the corresponding Lidar points. We also employ control points to adjust the point cloud for fine tuning the absolute position. To overcome the limitation of Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU) positioning system, we utilize Normal Distribution Transform (NDT) localization to refine the trajectory to solve the multi-scan dispersion issue. Experimental results show that the color point cloud reconstructed by the proposed MMS has a position error in centimeter-level accuracy, meeting the requirement of high definition (HD) maps for autonomous driving usage.
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Yang, Byungyun. "Developing a Mobile Mapping System for 3D GIS and Smart City Planning." Sustainability 11, no. 13 (July 7, 2019): 3713. http://dx.doi.org/10.3390/su11133713.
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The creation of augmented reality-related geographic information system (GIS) mapping applications has witnessed considerable advances in the technology of urban modeling; however, there are limitations to the technology that is currently used to create similar resources. The cost of the creation of the vehicle is an obstacle, and the rendering of textures of buildings is often lacking because of the distortion caused by the types of lenses that have been used. Generally, mobile mapping systems (MMSs) can extract detailed three-dimensional (3D) data with high quality texture information of the 3D building model. However, mapping urban areas by MMSs is expensive and requires advanced mathematical approaches with complicated steps. In particular, commercial MMS, which generally includes two GPS receivers, is an expensive device, costing ~$1 million. Thus, this research is aimed at developing a new MMS that semi-automatically produces high-quality texture information of 3D building models proposes a 3D urban model by hybrid approaches. Eventually, this study can support urban planners and people to improve their spatial perception and awareness of urban area for Smart City Planning.
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Elhashash, Mostafa, Hessah Albanwan, and Rongjun Qin. "A Review of Mobile Mapping Systems: From Sensors to Applications." Sensors 22, no. 11 (June 2, 2022): 4262. http://dx.doi.org/10.3390/s22114262.
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The evolution of mobile mapping systems (MMSs) has gained more attention in the past few decades. MMSs have been widely used to provide valuable assets in different applications. This has been facilitated by the wide availability of low-cost sensors, advances in computational resources, the maturity of mapping algorithms, and the need for accurate and on-demand geographic information system (GIS) data and digital maps. Many MMSs combine hybrid sensors to provide a more informative, robust, and stable solution by complementing each other. In this paper, we presented a comprehensive review of the modern MMSs by focusing on: (1) the types of sensors and platforms, discussing their capabilities and limitations and providing a comprehensive overview of recent MMS technologies available in the market; (2) highlighting the general workflow to process MMS data; (3) identifying different use cases of mobile mapping technology by reviewing some of the common applications; and (4) presenting a discussion on the benefits and challenges and sharing our views on potential research directions.
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Takahashi, G., and H. Masuda. "SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 325–31. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-325-2020.
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Abstract. Mobile Mapping System (MMS) equipped with a high-density LiDAR scanner is widely used for mapping. Various automatic mapping methods have been proposed for point clouds measured by the high-density LiDAR scanner on the MMS. However, careful parameter tuning is often required according to measurement conditions. In this paper, we propose a method to generate normalized scanlines from point clouds captured using the MMS. Normalized scanlines are useful to avoid parameter tuning depending on the measurement conditions. In order to evaluate the validity of our method, we extracted road boundaries with the same parameters from two point clouds measured under different conditions. In our evaluation, our method could detect almost the same road boundaries from the two point clouds using the same parameter settings.
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Li, Dan, and Wen Ying Su. "Dynamic Maintenance Data Mining of Traffic Sign Based on Mobile Mapping System." Applied Mechanics and Materials 455 (November 2013): 438–41. http://dx.doi.org/10.4028/www.scientific.net/amm.455.438.
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A dynamic traffic information system is an essential component of an intelligent transportation system. Mobile mapping system (MMS) is a new technique that can be used to improve capability of the information gathering. Article describes the measurement system based on mobile mapping system increased relevant software and hardware that can be used to collect maintenance information of traffic sign. Build a dynamic traffic sign maintenance information system with the function of rapid acquisition and analysis, these improve the accuracy and immediacy of traffic sign maintenance information processing.
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Soilán, M., B. Riveiro, J. Martínez-Sánchez, and P. Arias. "AUTOMATIC ROAD SIGN INVENTORY USING MOBILE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 717–23. http://dx.doi.org/10.5194/isprs-archives-xli-b3-717-2016.
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The periodic inspection of certain infrastructure features plays a key role for road network safety and preservation, and for developing optimal maintenance planning that minimize the life-cycle cost of the inspected features. Mobile Mapping Systems (MMS) use laser scanner technology in order to collect dense and precise three-dimensional point clouds that gather both geometric and radiometric information of the road network. Furthermore, time-stamped RGB imagery that is synchronized with the MMS trajectory is also available. In this paper a methodology for the automatic detection and classification of road signs from point cloud and imagery data provided by a LYNX Mobile Mapper System is presented. First, road signs are detected in the point cloud. Subsequently, the inventory is enriched with geometrical and contextual data such as orientation or distance to the trajectory. Finally, semantic content is given to the detected road signs. As point cloud resolution is insufficient, RGB imagery is used projecting the 3D points in the corresponding images and analysing the RGB data within the bounding box defined by the projected points. The methodology was tested in urban and road environments in Spain, obtaining global recall results greater than 95%, and F-score greater than 90%. In this way, inventory data is obtained in a fast, reliable manner, and it can be applied to improve the maintenance planning of the road network, or to feed a Spatial Information System (SIS), thus, road sign information can be available to be used in a Smart City context.
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Soilán, M., B. Riveiro, J. Martínez-Sánchez, and P. Arias. "AUTOMATIC ROAD SIGN INVENTORY USING MOBILE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 717–23. http://dx.doi.org/10.5194/isprsarchives-xli-b3-717-2016.
Full textAbstract:
The periodic inspection of certain infrastructure features plays a key role for road network safety and preservation, and for developing optimal maintenance planning that minimize the life-cycle cost of the inspected features. Mobile Mapping Systems (MMS) use laser scanner technology in order to collect dense and precise three-dimensional point clouds that gather both geometric and radiometric information of the road network. Furthermore, time-stamped RGB imagery that is synchronized with the MMS trajectory is also available. In this paper a methodology for the automatic detection and classification of road signs from point cloud and imagery data provided by a LYNX Mobile Mapper System is presented. First, road signs are detected in the point cloud. Subsequently, the inventory is enriched with geometrical and contextual data such as orientation or distance to the trajectory. Finally, semantic content is given to the detected road signs. As point cloud resolution is insufficient, RGB imagery is used projecting the 3D points in the corresponding images and analysing the RGB data within the bounding box defined by the projected points. The methodology was tested in urban and road environments in Spain, obtaining global recall results greater than 95%, and F-score greater than 90%. In this way, inventory data is obtained in a fast, reliable manner, and it can be applied to improve the maintenance planning of the road network, or to feed a Spatial Information System (SIS), thus, road sign information can be available to be used in a Smart City context.
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Salgues, H., H. Macher, and T. Landes. "EVALUATION OF MOBILE MAPPING SYSTEMS FOR INDOOR SURVEYS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-4/W1-2020 (September 3, 2020): 119–25. http://dx.doi.org/10.5194/isprs-archives-xliv-4-w1-2020-119-2020.
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Abstract. With their high recording rate of hundreds of thousands of points acquired per second, speed of execution and a remote acquisition mode, SLAM based mobile mapping systems (MMS) are a very powerful solution for capturing 3D point clouds in real time, simply by walking in the area of interest. Regarding indoor surveys, these MMS have been integrated in handheld or backpack solutions and become fast scanning sensors. Despite their advantages, the geometric accuracy of 3D point clouds guaranteed with these sensors is lower than the one reachable with static TLS. In this paper the effectiveness of two recent mobile mapping systems namely the GeoSLAM ZEB-REVO RT and the more recent GreenValley LiBackPack C50 is investigated for indoor surveys. In order to perform a reliable assessment study, several datasets produced with each sensor are compared to the high-cost georeferenced point cloud obtained with static laser scanning target-based technique.
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Sayama, Takahiro, Koji Matsumoto, Yuji Kuwano, and Kaoru Takara. "Application of Backpack-Mounted Mobile Mapping System and Rainfall–Runoff–Inundation Model for Flash Flood Analysis." Water 11, no. 5 (May 8, 2019): 963. http://dx.doi.org/10.3390/w11050963.
Full textAbstract:
Satellite remote sensing has been used effectively to estimate flood inundation extents in large river basins. In the case of flash floods in mountainous catchments, however, it is difficult to use remote sensing information. To compensate for this situation, detailed rainfall–runoff and flood inundation models have been utilized. Regardless of the recent technological advances in simulations, there has been a significant lack of data for validating such models, particularly with respect to local flood inundation depths. To estimate flood inundation depths, this study proposes using a backpack-mounted mobile mapping system (MMS) for post-flood surveys. Our case study in Northern Kyushu Island, which was affected by devastating flash floods in July 2017, suggests that the MMS can be used to estimate the inundation depth with an accuracy of 0.14 m. Furthermore, the landform change due to deposition of sediments could be estimated by the MMS survey. By taking into consideration the change of topography, the rainfall–runoff–inundation (RRI) model could reasonably reproduce the flood inundation compared with the MMS measurements. Overall, this study demonstrates the effective application of the MMS and RRI model for flash flood analysis in mountainous river catchments.
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Kulawiak, Marcin, and Witold Wycinka. "Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System." Metrology and Measurement Systems 24, no. 4 (December 20, 2017): 595–606. http://dx.doi.org/10.1515/mms-2017-0057.
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AbstractBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in the vicinity significantly alters the expected signal range. The paper presents a novel mobile Geographic Information System for measurement, mapping and local as well as online storage of Bluetooth beacon signal strength in semireal time. For the purpose of on-site geovisual analysis of the signal, the application integrates a dedicated interpolation algorithm optimized for low-power devices. The paper discusses the performance and quality of the mapping algorithms in several different test environments.
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Yamakawa, T., K. Fukano, R. Onodera, and H. Masuda. "REFINEMENT OF COLORED MOBILE MAPPING DATA USING INTENSITY IMAGES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 167–73. http://dx.doi.org/10.5194/isprsannals-iii-1-167-2016.
Full textAbstract:
Mobile mapping systems (MMS) can capture dense point-clouds of urban scenes. For visualizing realistic scenes using point-clouds, RGB colors have to be added to point-clouds. To generate colored point-clouds in a post-process, each point is projected onto camera images and a RGB color is copied to the point at the projected position. However, incorrect colors are often added to point-clouds because of the misalignment of laser scanners, the calibration errors of cameras and laser scanners, or the failure of GPS acquisition. In this paper, we propose a new method to correct RGB colors of point-clouds captured by a MMS. In our method, RGB colors of a point-cloud are corrected by comparing intensity images and RGB images. However, since a MMS outputs sparse and anisotropic point-clouds, regular images cannot be obtained from intensities of points. Therefore, we convert a point-cloud into a mesh model and project triangle faces onto image space, on which regular lattices are defined. Then we extract edge features from intensity images and RGB images, and detect their correspondences. In our experiments, our method worked very well for correcting RGB colors of point-clouds captured by a MMS.
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Yamakawa, T., K. Fukano, R. Onodera, and H. Masuda. "REFINEMENT OF COLORED MOBILE MAPPING DATA USING INTENSITY IMAGES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 167–73. http://dx.doi.org/10.5194/isprs-annals-iii-1-167-2016.
Full textAbstract:
Mobile mapping systems (MMS) can capture dense point-clouds of urban scenes. For visualizing realistic scenes using point-clouds, RGB colors have to be added to point-clouds. To generate colored point-clouds in a post-process, each point is projected onto camera images and a RGB color is copied to the point at the projected position. However, incorrect colors are often added to point-clouds because of the misalignment of laser scanners, the calibration errors of cameras and laser scanners, or the failure of GPS acquisition. In this paper, we propose a new method to correct RGB colors of point-clouds captured by a MMS. In our method, RGB colors of a point-cloud are corrected by comparing intensity images and RGB images. However, since a MMS outputs sparse and anisotropic point-clouds, regular images cannot be obtained from intensities of points. Therefore, we convert a point-cloud into a mesh model and project triangle faces onto image space, on which regular lattices are defined. Then we extract edge features from intensity images and RGB images, and detect their correspondences. In our experiments, our method worked very well for correcting RGB colors of point-clouds captured by a MMS.
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Maksimainen, Mikko, Matti T. Vaaja, Matti Kurkela, Juho-Pekka Virtanen, Arttu Julin, Kaisa Jaalama, and Hannu Hyyppä. "Nighttime Mobile Laser Scanning and 3D Luminance Measurement: Verifying the Outcome of Roadside Tree Pruning with Mobile Measurement of the Road Environment." ISPRS International Journal of Geo-Information 9, no. 7 (July 19, 2020): 455. http://dx.doi.org/10.3390/ijgi9070455.
Full textAbstract:
Roadside vegetation can affect the performance of installed road lighting. We demonstrate a workflow in which a car-mounted measurement system is used to assess the light-obstructing effect of roadside vegetation. The mobile mapping system (MMS) includes a panoramic camera system, laser scanner, inertial measurement unit, and satellite positioning system. The workflow and the measurement system were applied to a road section of Munkkiniemenranta, Helsinki, Finland, in 2015 and 2019. The relative luminance distribution on a road surface and the obstructing vegetation were measured before and after roadside vegetation pruning applying a luminance-calibrated mobile mapping system. The difference between the two measurements is presented, and the opportunities provided by the mobile 3D luminance measurement system are discussed.
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Sousa Guedes, Diana, Hélder Ribeiro, and Neftalí Sillero. "An Improved Mobile Mapping System to Detect Road-Killed Amphibians and Small Birds." ISPRS International Journal of Geo-Information 8, no. 12 (December 10, 2019): 565. http://dx.doi.org/10.3390/ijgi8120565.
Full textAbstract:
Roads represent a major source of mortality for many species. To mitigate road mortality, it is essential to know where collisions with vehicles are happening and which species and populations are most affected. For this, moving platforms such as mobile mapping systems (MMS) can be used to automatically detect road-killed animals on the road surface. We recently developed an MMS to detect road-killed amphibians, composed of a scanning system on a trailer. We present here a smaller and improved version of this system (MMS2) for detecting road-killed amphibians and small birds. It is composed of a stereo multi-spectral and high definition camera (ZED), a high-power processing laptop, a global positioning system (GPS) device, a support device, and a lighter charger. The MMS2 can be easily attached to any vehicle and the surveys can be performed by any person with or without sampling skills. To evaluate the system’s effectiveness, we performed several controlled and real surveys in the Évora district (Portugal). In real surveys, the system detected approximately 78% of the amphibians and birds present on surveyed roads (overlooking 22%) and generated approximately 17% of false positives. Our system can improve the implementation of conservation measures, saving time for researchers and transportation planning professionals.
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Campi, M., M. Falcone, and S. Sabbatini. "TOWARDS CONTINUOUS MONITORING OF ARCHITECTURE. TERRESTRIAL LASER SCANNING AND MOBILE MAPPING SYSTEM FOR THE DIAGNOSTIC PHASES OF THE CULTURAL HERITAGE." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-2/W1-2022 (February 25, 2022): 121–27. http://dx.doi.org/10.5194/isprs-archives-xlvi-2-w1-2022-121-2022.
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Abstract. In recent decades, the significant advances in digital technologies applied to cultural heritage have led to profound transformations in the activities of protection, conservation and enhancement. A current field of experimentation concerns 'rapid mapping' survey techniques with mobile mapping system (MMS). The use of these methodologies is increasingly widespread for the diagnostic and monitoring phases of the architectures. The potential of these techniques are manifold: these systems record, in a short time, a large number of information with a rather high level of accuracy. In particular, the research presented here has studied an 'innovative' Lidar mobile mapping methodology, NavVis VLX, with experimental perspectives, for the survey of the Cripta of the Cathedral of San Matteo in Salerno (Italy).
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Ishikawa, Kiichiro, Yoshiharu Amano, Takumi Hashizume, Jun-ichi Takiguchi, and Naoyuki Kajiwara. "A Mobile Mapping System for Precise Road Line Localization Using a Single Camera and 3D Road Model." Journal of Robotics and Mechatronics 19, no. 2 (April 20, 2007): 174–80. http://dx.doi.org/10.20965/jrm.2007.p0174.
Full textAbstract:
Precise highway alignment data to be used in car navigation and ITS to increase driving safety must be kept up-to-date and accurate. A Mobile Mapping System (MMS) provides a highway alignment database and offers unparalleled productivity when combined with navigation and videogrammetry tools. The MMS we propose features a GPS/Dead Reckoning (DR) combined navigation system, a three-axis GPS-Gyro/Inertial Measurement Unit (IMU), laser scanners, nearly horizontal cameras, and network-based Positioning Augmentation Services (PASTM) (Mitsubishi Electric Corporation) and measures center-line and side-line locations precisely based on a 3D road surface model. The carrier-phased D-GPS/DR navigation system and GPS-Gyro/IMU conducts highly accurate positioning in centimeters and posture estimation at 0.073° rms for heading, 0.064° rms for pitch, and 0.116° for roll. It provides 0.095 m rms accuracy for both center-line and side-line measurement when GPS visibility is sufficient. A comparison of accuracy between static RTK-GPS measurement and MMS measurement on the Tateyama Kurobe alpine route confirmed MMS dynamic measurement accuracy and effectiveness.
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Fissore, F., F. Pirotti, and A. Vettore. "OPEN SOURCE WEB TOOL FOR TRACKING IN A LOWCOST MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W8 (November 13, 2017): 99–104. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w8-99-2017.
Full textAbstract:
During the last decade several Mobile Mapping Systems (MMSs), i.e. systems able to acquire efficiently three dimensional data using moving sensors (Guarnieri et al., 2008, Schwarz and El-Sheimy, 2004), have been developed. Research and commercial products have been implemented on terrestrial, aerial and marine platforms, and even on human-carried equipment, e.g. backpack (Lo et al., 2015, Nex and Remondino, 2014, Ellum and El-Sheimy, 2002, Leica Pegasus backpack, 2016, Masiero et al., 2017, Fissore et al., 2018).<br><br> Such systems are composed of an integrated array of time-synchronised navigation sensors and imaging sensors mounted on a mobile platform (Puente et al., 2013, Tao and Li, 2007). Usually the MMS implies integration of different types of sensors, such as GNSS, IMU, video camera and/or laser scanners that allow accurate and quick mapping (Li, 1997, Petrie, 2010, Tao, 2000). The typical requirement of high-accuracy 3D georeferenced reconstruction often makes such systems quite expensive. Indeed, at time of writing most of the terrestrial MMSs on the market have a cost usually greater than 50000, which might be expensive for certain applications (Ellum and El-Sheimy, 2002, Piras et al., 2008). In order to allow best performance sensors have to be properly calibrated (Dong et al., 2007, Ellum and El-Sheimy, 2002).<br><br> Sensors in MMSs are usually integrated and managed through a dedicated software, which is developed ad hoc for the devices mounted on the mobile platform and hence tailored for the specific used sensors. Despite the fact that commercial solutions are complete, very specific and particularly related to the typology of survey, their price is a factor that restricts the number of users and the possible interested sectors.<br><br> This paper describes a (relatively low cost) terrestrial Mobile Mapping System developed at the University of Padua (TESAF, Department of Land Environment Agriculture and Forestry) by the research team in CIRGEO, in order to test an alternative solution to other more expensive MMSs. The first objective of this paper is to report on the development of a prototype of MMS for the collection of geospatial data based on the assembly of low cost sensors managed through a web interface developed using open source libraries. The main goal is to provide a system accessible by any type of user, and flexible to any type of upgrade or introduction of new models of sensors or versions thereof. After a presentation of the hardware components used in our system, a more detailed description of the software developed for the management of the MMS will be provided, which is the part of the innovation of the project. According to the worldwide request for having big data available through the web from everywhere in the world (Pirotti et al., 2011), the proposed solution allows to retrieve data from a web interface Figure 4. Actually, this is part of a project for the development of a new web infrastructure in the University of Padua (but it will be available for external users as well), in order to ease collaboration between researchers from different areas.<br><br> Finally, strengths, weaknesses and future developments of the low cost MMS are discussed.
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Li, Yunzhi, Yuntian Bai, and Mengke Wang. "A Self-Calibration Method for Boresight Error of Mobile Mapping System." E3S Web of Conferences 206 (2020): 03010. http://dx.doi.org/10.1051/e3sconf/202020603010.
Full textAbstract:
The boresight error is one of the main error sources of the Mobile Mapping System(MMS), which directly affects the overall accuracy and quality of the laser point cloud. Unideal boresight error estimation seriously reduces the point cloud registration accuracy. When there is a feature place in the laser point cloud, the boresight error will cause the feature plane to deviate from the real plane. In order to solve the above problems, a visual axis calibration method for a mobile surveying and mapping system based on known feature planes is proposed. According to the plane features of 3D scene, the Gauss-Helmert adjustment model is established, and the normal equation for calculating the boresight error is derived. This is a simple and reliable calibration method.
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Chu, Chien-Hsun, and Kai-Wei Chiang. "THE PERFORMANCE OF A TIGHT INS/GNSS/PHOTOGRAMMETRIC INTEGRATION SCHEME FOR LAND BASED MMS APPLICATIONS IN GNSS DENIED ENVIRONMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 551–57. http://dx.doi.org/10.5194/isprsarchives-xli-b1-551-2016.
Full textAbstract:
The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.
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Chu, Chien-Hsun, and Kai-Wei Chiang. "THE PERFORMANCE OF A TIGHT INS/GNSS/PHOTOGRAMMETRIC INTEGRATION SCHEME FOR LAND BASED MMS APPLICATIONS IN GNSS DENIED ENVIRONMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 551–57. http://dx.doi.org/10.5194/isprs-archives-xli-b1-551-2016.
Full textAbstract:
The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.
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Li, Y., J. Fan, Y. Huang, and Z. Chen. "LIDAR-INCORPORATED TRAFFIC SIGN DETECTION FROM VIDEO LOG IMAGES OF MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 661–68. http://dx.doi.org/10.5194/isprs-archives-xli-b1-661-2016.
Full textAbstract:
Mobile Mapping System (MMS) simultaneously collects the Lidar points and video log images in a scenario with the laser profiler and digital camera. Besides the textural details of video log images, it also captures the 3D geometric shape of point cloud. It is widely used to survey the street view and roadside transportation infrastructure, such as traffic sign, guardrail, etc., in many transportation agencies. Although many literature on traffic sign detection are available, they only focus on either Lidar or imagery data of traffic sign. Based on the well-calibrated extrinsic parameters of MMS, 3D Lidar points are, the first time, incorporated into 2D video log images to enhance the detection of traffic sign both physically and visually. Based on the local elevation, the 3D pavement area is first located. Within a certain distance and height of the pavement, points of the overhead and roadside traffic signs can be obtained according to the setup specification of traffic signs in different transportation agencies. The 3D candidate planes of traffic signs are then fitted using the RANSAC plane-fitting of those points. By projecting the candidate planes onto the image, Regions of Interest (ROIs) of traffic signs are found physically with the geometric constraints between laser profiling and camera imaging. The Random forest learning of the visual color and shape features of traffic signs is adopted to validate the sign ROIs from the video log images. The sequential occurrence of a traffic sign among consecutive video log images are defined by the geometric constraint of the imaging geometry and GPS movement. Candidate ROIs are predicted in this temporal context to double-check the salient traffic sign among video log images. The proposed algorithm is tested on a diverse set of scenarios on the interstate highway G-4 near Beijing, China under varying lighting conditions and occlusions. Experimental results show the proposed algorithm enhances the rate of detecting traffic signs with the incorporation of the 3D planar constraint of their Lidar points. It is promising for the robust and large-scale survey of most transportation infrastructure with the application of MMS.
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Li, Y., J. Fan, Y. Huang, and Z. Chen. "LIDAR-INCORPORATED TRAFFIC SIGN DETECTION FROM VIDEO LOG IMAGES OF MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 661–68. http://dx.doi.org/10.5194/isprsarchives-xli-b1-661-2016.
Full textAbstract:
Mobile Mapping System (MMS) simultaneously collects the Lidar points and video log images in a scenario with the laser profiler and digital camera. Besides the textural details of video log images, it also captures the 3D geometric shape of point cloud. It is widely used to survey the street view and roadside transportation infrastructure, such as traffic sign, guardrail, etc., in many transportation agencies. Although many literature on traffic sign detection are available, they only focus on either Lidar or imagery data of traffic sign. Based on the well-calibrated extrinsic parameters of MMS, 3D Lidar points are, the first time, incorporated into 2D video log images to enhance the detection of traffic sign both physically and visually. Based on the local elevation, the 3D pavement area is first located. Within a certain distance and height of the pavement, points of the overhead and roadside traffic signs can be obtained according to the setup specification of traffic signs in different transportation agencies. The 3D candidate planes of traffic signs are then fitted using the RANSAC plane-fitting of those points. By projecting the candidate planes onto the image, Regions of Interest (ROIs) of traffic signs are found physically with the geometric constraints between laser profiling and camera imaging. The Random forest learning of the visual color and shape features of traffic signs is adopted to validate the sign ROIs from the video log images. The sequential occurrence of a traffic sign among consecutive video log images are defined by the geometric constraint of the imaging geometry and GPS movement. Candidate ROIs are predicted in this temporal context to double-check the salient traffic sign among video log images. The proposed algorithm is tested on a diverse set of scenarios on the interstate highway G-4 near Beijing, China under varying lighting conditions and occlusions. Experimental results show the proposed algorithm enhances the rate of detecting traffic signs with the incorporation of the 3D planar constraint of their Lidar points. It is promising for the robust and large-scale survey of most transportation infrastructure with the application of MMS.
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Fassi, F., and L. Perfetti. "BACKPACK MOBILE MAPPING SOLUTION FOR DTM EXTRACTION OF LARGE INACCESSIBLE SPACES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W15 (August 22, 2019): 473–80. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w15-473-2019.
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<p><strong>Abstract.</strong> The paper presents the case study of the complete 3D survey of the area of the Fort of Pietole in Borgo Virgilio using the Leica Pegasus Backpack wearable Mobile Mapping System (MMS). Surveying the site is challenging because of its complex topology on the one hand (with notably narrow passages) and because of the presence of vegetation on the other. The framework within which this research takes place is the Fort of Pietole survey project that aims at the extraction of the Digital Terrain Model (DTM) of the area and the georeferencing of the fort defensive structures. The requirement of the project is the 3D reconstruction of the whole area at an accuracy that stands between a big scale environmental survey and a small-scale architectonic survey (1&thinsp;:&thinsp;500).</p> <p>The project is the opportunity to discuss the state of the art of wearable MMS, and to test the versatility and accuracy outcomes of the Pegasus Backpack under varying and challenging condition (indoor-outdoor, even-uneven pavement, satellite covered-denied areas) with the ambitious goal to use only the backpack MMS to record all the data from the DTM to the indoor narrow structures.</p>
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Tianen, Chen, Kohei Yamamoto, and Kikuo Tachibana. "A METHOD OF GENERATING PANORAMIC STREET STRIP IMAGE MAP WITH MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 537–44. http://dx.doi.org/10.5194/isprsarchives-xli-b1-537-2016.
Full textAbstract:
This paper explores a method of generating panoramic street strip image map which is called as “Pano-Street” here and contains both sides, ground surface and overhead part of a street with a sequence of 360° panoramic images captured with Point Grey’s Ladybug3 mounted on the top of Mitsubishi MMS-X 220 at 2m intervals along the streets in urban environment. On-board GPS/IMU, speedometer and post sequence image analysis technology such as bundle adjustment provided much more accuracy level position and attitude data for these panoramic images, and laser data. The principle for generating panoramic street strip image map is similar to that of the traditional aero ortho-images. A special 3D DEM(3D-Mesh called here) was firstly generated with laser data, the depth map generated from dense image matching with the sequence of 360° panoramic images, or the existing GIS spatial data along the MMS trajectory, then all 360° panoramic images were projected and stitched on the 3D-Mesh with the position and attitude data. This makes it possible to make large scale panoramic street strip image maps for most types of cities, and provides another kind of street view way to view the 360° scene along the street by avoiding the switch of image bubbles like Google Street View and Bing Maps Streetside.
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Tianen, Chen, Kohei Yamamoto, and Kikuo Tachibana. "A METHOD OF GENERATING PANORAMIC STREET STRIP IMAGE MAP WITH MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 537–44. http://dx.doi.org/10.5194/isprs-archives-xli-b1-537-2016.
Full textAbstract:
This paper explores a method of generating panoramic street strip image map which is called as “Pano-Street” here and contains both sides, ground surface and overhead part of a street with a sequence of 360° panoramic images captured with Point Grey’s Ladybug3 mounted on the top of Mitsubishi MMS-X 220 at 2m intervals along the streets in urban environment. On-board GPS/IMU, speedometer and post sequence image analysis technology such as bundle adjustment provided much more accuracy level position and attitude data for these panoramic images, and laser data. The principle for generating panoramic street strip image map is similar to that of the traditional aero ortho-images. A special 3D DEM(3D-Mesh called here) was firstly generated with laser data, the depth map generated from dense image matching with the sequence of 360° panoramic images, or the existing GIS spatial data along the MMS trajectory, then all 360° panoramic images were projected and stitched on the 3D-Mesh with the position and attitude data. This makes it possible to make large scale panoramic street strip image maps for most types of cities, and provides another kind of street view way to view the 360° scene along the street by avoiding the switch of image bubbles like Google Street View and Bing Maps Streetside.
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Perng, Jau Woei, Chia Hui Tai, Chia Hao Kuo, and Li Shan Ma. "3D Environment Mapping and Pothole Detection for a Mobile Robot." Applied Mechanics and Materials 431 (October 2013): 287–92. http://dx.doi.org/10.4028/www.scientific.net/amm.431.287.
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This paper proposes a 3D environment mapping and pothole detection system by using a laser range finder for a mobile robot. The robot also equips two rotary encoders and an inertial measurement unit to deal with dead reckoning (DR). Through the coordinate transform method from 2D to 3D, each point in 3D coordinate could be calculated. This method is called mobile mapping system (MMS). In addition, the result for road damage is often caused by potholes. Therefore, the pothole detection is considered here by using a laser range finder and a camera. A human-machine interface is designed to record the data on the road including the location and environment. The experiment has been tested on the university road.
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Bonfanti, C., G. Patrucco, S. Perri, G. Sammartano, and A. Spanò. "A NEW INDOOR LIDAR-BASED MMS CHALLENGING COMPLEX ARCHITECTURAL ENVIRONMENTS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-M-1-2021 (August 28, 2021): 79–86. http://dx.doi.org/10.5194/isprs-archives-xlvi-m-1-2021-79-2021.
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Abstract. The use of moving devices equipped with range- and image-based sensor, generically defined Mobile Mapping systems (MMS), have been quite a disruptive innovation in the development of Geomatics techniques for 3D surveying large indoor-outdoor spaces and offer multiple solutions. The recent expansion of portable devices in the form of trolleys, backpacks, handheld tools largely implements SLAM (Simultaneous Localization and Mapping) algorithms and technology based on both Lidar and/or visual solutions for answering to the positioning and the 3D reconstruction problems. The research on MMS is directed to improve both multi-sensor integration implementation and usability of systems in diversified use contexts and application fields. The aim of the presented research is the evaluation of the potential of the Swift system recently developed by FARO Technologies, that has been fine-tuned for regular and large extent interiors mapping (such as factories, hospitals, airports, offices). The work tries to preliminary investigate the data delivery and usability of the integrated system. This is based on three elements mounted on a sliding trolley moved by the operator walking: the ScanPlan profilometer working for the 2D SLAM mapping, the static TLS Focus S-series, and the smartphone managing the sensors operation and the acquisition progress. The evaluation strategy undertaken will be based on the global and local performance analysis related to the trajectory, the data accuracy, the metric content and consistency. Two test studies belonging to the 20th century. architecture are presented in a preliminary framework of evaluation and validation: a Liberty-style cinema and the Torino Esposizioni Hall B designed in ferrocement by pier Luigi Nervi.
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MANO, Koji, Kazunori ISHII, Masataka HIRAO, Kikuo TACHIBANA, Mitsunori YOSHIMURA, Devrim AKCA, and Armin GRUEN. "A Study on Accuracy Investigation of Point Clouds Generated by the Mobile Mapping System (MMS)." Journal of the Japan society of photogrammetry and remote sensing 51, no. 4 (2012): 186–200. http://dx.doi.org/10.4287/jsprs.51.186.
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Lee, Jisang, Suhong Yoo, Seunghwan Hong, Mohammad Gholami Farkoushi, Junsu Bae, Ilsuk Park, and Hong-Gyoo Sohn. "Automated Algorithm for Removing Clutter Objects in MMS Point Cloud for 3D Road Mapping." Sensors 20, no. 15 (July 22, 2020): 4076. http://dx.doi.org/10.3390/s20154076.
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Road information high definition maps (HD map) contain information about the facilities around the roads and are often constructed through a mobile mapping system (MMS). Although constructing an HD map is essential for road maintenance and the application of autonomous driving in the future, it is problematic to acquire the data of objects other than the facilities in an unstructured form while operating the MMS. In this study, the researchers define this object data as clutter objects and present a method of automatic removal using characteristics of the MMS and image segmentation techniques. By applying the method to 10 KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago) datasets, clutter objects were removed with an average overall accuracy of 91% with 0% (0.448%) error of commission for the complete point cloud map.
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Matsumoto, H., Y. Mori, and H. Masuda. "EXTRACTION AND SHAPE RECONSTRUCTION OF GUARDRAILS USING MOBILE MAPPING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1061–68. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1061-2019.
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<p><strong>Abstract.</strong> The mobile mapping system (MMS) can acquire dense point-clouds of roads and roadside features. Roads are often separated into roadways and walkways in many urban areas. Since guardrails are installed to separate roadways and sidewalks, it is important to detect guardrails from point-clouds and reconstruct their 3D models for 3D street maps. Since there are a large variety of designs for guardrails in Japan, flexible methods are required for detection and reconstruction of guardrails. In this paper, we propose a new method for extracting guardrails from point-clouds, and reconstructing their 3D models. Since the MMS captures point-clouds and camera images synchronously, guardrails are detected using both point-clouds and images. In our method, point-clouds are segmented into small segments, and corresponding images are cropped from camera images. Then cropped images are classified into two classes of guardrails and others using the convolutional neural network. When guardrail points are obtained, 3D models of guardrails are reconstructed. However, point-clouds of guardrails are too sparse to reconstruct 3D shapes when guardrails consist of thin pipes. Since the same unit shape repeatedly appears in a guardrail, we create dense point-clouds by superimposing points of unit shapes. Then we reconstruct 3D shapes of pipes, beams, and poles of guardrails. In our evaluation using point-clouds in urban areas, our method could achieve good results of extraction and shape reconstruction of guardrails.</p>
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Yao, Q., B. Tan, and Y. Huang. "FAST DRAWING OF TRAFFIC SIGN USING MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 937–44. http://dx.doi.org/10.5194/isprs-archives-xli-b3-937-2016.
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Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a traffic sign.The proposed algorithm is tested with a diverse set of images that are taken inWuhan, China with theMMS ofWuhan University. Experimental results demonstrate that the proposed algorithm can detect traffic signs at the rate of over 80% in around 10 milliseconds. It is promising for the large-scale traffic sign survey and change detection using the mobile mapping system.
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Yao, Q., B. Tan, and Y. Huang. "FAST DRAWING OF TRAFFIC SIGN USING MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 937–44. http://dx.doi.org/10.5194/isprsarchives-xli-b3-937-2016.
Full textAbstract:
Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a traffic sign.The proposed algorithm is tested with a diverse set of images that are taken inWuhan, China with theMMS ofWuhan University. Experimental results demonstrate that the proposed algorithm can detect traffic signs at the rate of over 80% in around 10 milliseconds. It is promising for the large-scale traffic sign survey and change detection using the mobile mapping system.
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Mori, Y., K. Kohira, and H. Masuda. "CLASSIFICATION OF POLE-LIKE OBJECTS USING POINT CLOUDS AND IMAGES CAPTURED BY MOBILE MAPPING SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 731–38. http://dx.doi.org/10.5194/isprs-archives-xlii-2-731-2018.
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The vehicle-based mobile mapping system (MMS) is effective for capturing 3D shapes and images of roadside objects. The laser scanner and cameras on the MMS capture point-clouds and sequential digital images synchronously during driving. In this paper, we propose a method for detecting and classifying pole-like objects using both point-clouds and images captured using the MMS. In our method, pole-like objects are detected from point-clouds, and then target objects, which are objects attached to poles, are extracted for identifying the types of pole-like objects. For associating each target object with images, the points of the target object are projected onto images, and the image of the target object is cropped. Each pole-like object is represented as a feature vector, which are calculated from point-clouds and images. The feature values of a point-cloud are calculated by point processing, and the ones of the cropped image are calculated using a convolutional neural network. The feature values of point-clouds and images are unified, and they are used as the input to machine learning. In experiments, we classified pole-like objects using three methods. The first method used only point-clouds, the second used only images, and the third used both point-clouds and images. The experimental results showed that the third method could most accurately classify pole-like objects.
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Ishikawa, Kiichiro, Yoshiharu Amano, and Takumi Hashizume. "Path Planning for Mobile Mapping System Considering the Geometry of the GPS Satellite." Journal of Robotics and Mechatronics 25, no. 3 (June 20, 2013): 545–52. http://dx.doi.org/10.20965/jrm.2013.p0545.
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In this paper, we propose a path planning method for a Mobile Mapping System (MMS) considering GPS geometry for the purpose of increasing GPS availability. We calculate Position Dilution of Precision (PDOP) using aerial laser survey data that provides geography and height of buildings near roads. PDOP is used for weighting road network data. By using the Chinese postman problem, we then calculate the optimum path that passes through all routes at least once. We describe currentMMS operation first and clear up problems with the current method. We then describe the proposed method in detail. Finally, we conduct evaluation tests and describe results in detail. The evaluation test verifies that the proposed method increases the GPS FIX ratio by 5% under the same GPS geometry and proves the effectiveness of the proposed method.