Journal articles: 'SfM-MVS'

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Smith, M. W., J. L. Carrivick, and D. J. Quincey. "Structure from motion photogrammetry in physical geography." Progress in Physical Geography: Earth and Environment 40, no. 2 (November 26, 2015): 247–75. http://dx.doi.org/10.1177/0309133315615805.

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Accurate, precise and rapid acquisition of topographic data is fundamental to many sub-disciplines of physical geography. Technological developments over the past few decades have made fully distributed data sets of centimetric resolution and accuracy commonplace, yet the emergence of Structure from Motion (SfM) with Multi-View Stereo (MVS) in recent years has revolutionised three-dimensional topographic surveys in physical geography by democratising data collection and processing. SfM-MVS originates from the fields of computer vision and photogrammetry, requires minimal expensive equipment or specialist expertise and, under certain conditions, can produce point clouds of comparable quality to existing survey methods (e.g. Terrestrial Laser Scanning). Consequently, applications of SfM-MVS in physical geography have multiplied rapidly. There are many practical options available to physical geographers when planning a SfM-MVS survey (e.g. platforms, cameras, software), yet, many SfM-MVS end-users are uncertain as to the errors associated with each choice and, perhaps most fundamentally, the processes actually taking place as part of the SfM-MVS workflow. This paper details the typical workflow applied by SfM-MVS software packages, reviews practical details of implementing SfM-MVS, combines existing validation studies to assess practically achievable data quality and reviews the range of applications of SfM-MVS in physical geography. The flexibility of the SfM-MVS approach complicates attempts to validate SfM-MVS robustly as each individual validation study will use a different approach (e.g. platform, camera, georeferencing method, etc.). We highlight the need for greater transparency in SfM-MVS processing and enhanced ability to adjust parameters that determine survey quality. Looking forwards, future prospects of SfM-MVS in physical geography are identified through discussion of more recent developments in the fields of image analysis and computer vision.

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Berra, E. F., and M. V. Peppa. "ADVANCES AND CHALLENGES OF UAV SFM MVS PHOTOGRAMMETRY AND REMOTE SENSING: SHORT REVIEW." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (December 22, 2020): 267–72. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-267-2020.

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Abstract. Interest in Unnamed Aerial Vehicle (UAV)-sourced data and Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) photogrammetry has seen a dramatic expansion over the last decade, revolutionizing the fields of aerial remote sensing and mapping. This literature review provides a summary overview on the recent developments and applications of light-weight UAVs and on the widely-accepted SfM - MVS approach. Firstly, the advantages and limitations of UAV remote sensing systems are discussed, followed by an identification of the different UAV and miniaturised sensor models applied to numerous disciplines, showing the range of systems and sensor types utilised recently. Afterwards, a concise list of advantages and challenges of UAV SfM-MVS is provided and discussed. Overall, the accuracy and quality of the SfM-MVS-derived products (e.g. orthomosaics, digital surface model) depends on the quality of the UAV data set, characteristics of the study area and processing tools used. Continued development and investigation are necessary to better determine the quality, precision and accuracy of UAV SfM-MVS derived outputs.

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Kalacska, Margaret, Oliver Lucanus, Leandro Sousa, Thiago Vieira, and Juan Arroyo-Mora. "Freshwater Fish Habitat Complexity Mapping Using Above and Underwater Structure-From-Motion Photogrammetry." Remote Sensing 10, no. 12 (November 29, 2018): 1912. http://dx.doi.org/10.3390/rs10121912.

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Substrate complexity is strongly related to biodiversity in aquatic habitats. We illustrate a novel framework, based on Structure-from-Motion photogrammetry (SfM) and Multi-View Stereo (MVS) photogrammetry, to quantify habitat complexity in freshwater ecosystems from Unmanned Aerial Vehicle (UAV) and underwater photography. We analysed sites in the Xingu river basin, Brazil, to reconstruct the 3D structure of the substrate and identify and map habitat classes important for maintaining fish assemblage biodiversity. From the digital models we calculated habitat complexity metrics including rugosity, slope and 3D fractal dimension. The UAV based SfM-MVS products were generated at a ground sampling distance (GSD) of 1.20–2.38 cm while the underwater photography produced a GSD of 1 mm. Our results show how these products provide spatially explicit complexity metrics, which are more comprehensive than conventional arbitrary cross sections. Shallow neural network classification of SfM-MVS products of substrate exposed in the dry season resulted in high accuracies across classes. UAV and underwater SfM-MVS is robust for quantifying freshwater habitat classes and complexity and should be chosen whenever possible over conventional methods (e.g., chain-and-tape) because of the repeatability, scalability and multi-dimensional nature of the products. The SfM-MVS products can be used to identify high priority freshwater sectors for conservation, species occurrences and diversity studies to provide a broader indication for overall fish species diversity and provide repeatability for monitoring change over time.

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Tavani, Stefano, Pablo Granado, Umberto Riccardi, Thomas Seers, and Amerigo Corradetti. "Terrestrial SfM-MVS photogrammetry from smartphone sensors." Geomorphology 367 (October 2020): 107318. http://dx.doi.org/10.1016/j.geomorph.2020.107318.

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Warfield, Angus D., and Javier X. Leon. "Estimating Mangrove Forest Volume Using Terrestrial Laser Scanning and UAV-Derived Structure-from-Motion." Drones 3, no. 2 (April 1, 2019): 32. http://dx.doi.org/10.3390/drones3020032.

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Mangroves provide a variety of ecosystem services, which can be related to their structuralcomplexity and ability to store carbon in the above ground biomass (AGB). Quantifying AGB inmangroves has traditionally been conducted using destructive, time-consuming, and costlymethods, however, Structure-from-Motion Multi-View Stereo (SfM-MVS) combined withunmanned aerial vehicle (UAV) imagery may provide an alternative. Here, we compared the abilityof SfM-MVS with terrestrial laser scanning (TLS) to capture forest structure and volume in threemangrove sites of differing stand age and species composition. We describe forest structure in termsof point density, while forest volume is estimated as a proxy for AGB using the surface differencingmethod. In general, SfM-MVS poorly captured mangrove forest structure, but was efficient incapturing the canopy height for volume estimations. The differences in volume estimations betweenTLS and SfM-MVS were higher in the juvenile age site (42.95%) than the mixed (28.23%) or mature(12.72%) age sites, with a higher stem density affecting point capture in both methods. These resultscan be used to inform non-destructive, cost-effective, and timely assessments of forest structure orAGB in mangroves in the future.

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Tavani, Stefano, Antonio Pignalosa, Amerigo Corradetti, Marco Mercuri, Luca Smeraglia, Umberto Riccardi, Thomas Seers, Terry Pavlis, and Andrea Billi. "Photogrammetric 3D Model via Smartphone GNSS Sensor: Workflow, Error Estimate, and Best Practices." Remote Sensing 12, no. 21 (November 4, 2020): 3616. http://dx.doi.org/10.3390/rs12213616.

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Geotagged smartphone photos can be employed to build digital terrain models using structure from motion-multiview stereo (SfM-MVS) photogrammetry. Accelerometer, magnetometer, and gyroscope sensors integrated within consumer-grade smartphones can be used to record the orientation of images, which can be combined with location information provided by inbuilt global navigation satellite system (GNSS) sensors to geo-register the SfM-MVS model. The accuracy of these sensors is, however, highly variable. In this work, we use a 200 m-wide natural rocky cliff as a test case to evaluate the impact of consumer-grade smartphone GNSS sensor accuracy on the registration of SfM-MVS models. We built a high-resolution 3D model of the cliff, using an unmanned aerial vehicle (UAV) for image acquisition and ground control points (GCPs) located using a differential GNSS survey for georeferencing. This 3D model provides the benchmark against which terrestrial SfM-MVS photogrammetry models, built using smartphone images and registered using built-in accelerometer/gyroscope and GNSS sensors, are compared. Results show that satisfactory post-processing registrations of the smartphone models can be attained, requiring: (1) wide acquisition areas (scaling with GNSS error) and (2) the progressive removal of misaligned images, via an iterative process of model building and error estimation.

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Piermattei, Livia, Luca Carturan, Fabrizio de Blasi, Paolo Tarolli, Giancarlo Dalla Fontana, Antonio Vettore, and Norbert Pfeifer. "Suitability of ground-based SfM–MVS for monitoring glacial and periglacial processes." Earth Surface Dynamics 4, no. 2 (May 20, 2016): 425–43. http://dx.doi.org/10.5194/esurf-4-425-2016.

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Abstract. Photo-based surface reconstruction is rapidly emerging as an alternative survey technique to lidar (light detection and ranging) in many fields of geoscience fostered by the recent development of computer vision algorithms such as structure from motion (SfM) and dense image matching such as multi-view stereo (MVS). The objectives of this work are to test the suitability of the ground-based SfM–MVS approach for calculating the geodetic mass balance of a 2.1 km2 glacier and for detecting the surface displacement of a neighbouring active rock glacier located in the eastern Italian Alps. The photos were acquired in 2013 and 2014 using a digital consumer-grade camera during single-day field surveys. Airborne laser scanning (ALS, otherwise known as airborne lidar) data were used as benchmarks to estimate the accuracy of the photogrammetric digital elevation models (DEMs) and the reliability of the method. The SfM–MVS approach enabled the reconstruction of high-quality DEMs, which provided estimates of glacial and periglacial processes similar to those achievable using ALS. In stable bedrock areas outside the glacier, the mean and the standard deviation of the elevation difference between the SfM–MVS DEM and the ALS DEM was −0.42 ± 1.72 and 0.03 ± 0.74 m in 2013 and 2014, respectively. The overall pattern of elevation loss and gain on the glacier were similar with both methods, ranging between −5.53 and + 3.48 m. In the rock glacier area, the elevation difference between the SfM–MVS DEM and the ALS DEM was 0.02 ± 0.17 m. The SfM–MVS was able to reproduce the patterns and the magnitudes of displacement of the rock glacier observed by the ALS, ranging between 0.00 and 0.48 m per year. The use of natural targets as ground control points, the occurrence of shadowed and low-contrast areas, and in particular the suboptimal camera network geometry imposed by the morphology of the study area were the main factors affecting the accuracy of photogrammetric DEMs negatively. Technical improvements such as using an aerial platform and/or placing artificial targets could significantly improve the results but run the risk of being more demanding in terms of costs and logistics.

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Moritani, R., S. Kanai, H. Date, Y. Niina, and R. Honma. "PLAUSIBLE RECONSTRUCTION OF AN APPROXIMATED MESH MODEL FOR NEXT-BEST VIEW PLANNING OF SFM-MVS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 465–71. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-465-2020.

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Abstract. Structure-from-Motion (SfM) and Multi-View Stereo (MVS) are widely used methods in three dimensional (3D) model reconstruction for an infrastructure maintenance purpose. However, if a set of images is not captured from well-placed positions, the final dense model can contain low-quality regions. Since MVS requires a much longer processing time than SfM as larger amounts of images are provided, it is impossible for surveyors to wait for the SfM–MVS process to complete and evaluate the geometric quality of a final dense model on-site. This challenge results in response inefficiency and the deterioration of dense models in 3D model reconstruction. If the quality of the final dense model can be predicted immediately after SfM, it will be possible to revalidate the images much earlier and to obtain the dense model with better quality than the existing SfM–MVS process. Therefore, we propose a method for reconstructing a more plausible 3D mesh model that accurately approximates the geometry of the final dense model only from sparse point clouds generated from SfM. This approximated mesh model can be generated using Delaunay triangulation for the sparse point clouds and triangle as well as tetrahedron filtering. The approximated model can be used to predict the geometric quality of the final dense model and for an optimization-based view planning. Some experimental results showed that our method is effective in predicting the quality of the final dense model and finding the potentially degraded regions. Moreover, it was confirmed that the average reconstruction errors of the dense model generated by the optimization-based view planning went below tens of millimeters and falls within an acceptable range for an infrastructure maintenance purpose.

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Kaneda, Akihiro, Tomomi Nakagawa, Kohei Tamura, Koji Noshita, and Hisashi Nakao. "A proposal of a new automated method for SfM/MVS 3D reconstruction through comparisons of 3D data by SfM/MVS and handheld laser scanners." PLOS ONE 17, no. 7 (July 20, 2022): e0270660. http://dx.doi.org/10.1371/journal.pone.0270660.

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SfM/MVS photogrammetry has received increasing attention due to its convenience, broadening the range of its applications into archaeology and anthropology. Because the accuracy of SfM/MVS depends on photography, one important issue is that incorrect or low-density point clouds are found in 3D models due to poor overlapping between images. A systematic way of taking photographs solve these problems, though it has not been well established and the accuracy has not been examined either, with some exceptions. The present study aims to (i) develop an efficient method for recording pottery using an automated turntable and (ii) assess its accuracy through a comparison with 3D models made by laser scanning. We recorded relatively simple pottery manufactured by prehistoric farmers in the Japanese archipelago using SfM/MVS photogrammetry and laser scanning. Further, by measuring the Hausdorff distance between 3D models made using these two methods, we show that their difference is negligibly small, suggesting that our method is sufficiently accurate to record pottery.

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Piermattei, L., L. Carturan, F. de Blasi, P. Tarolli, G. Dalla Fontana, A. Vettore, and N. Pfeifer. "Analysis of glacial and periglacial processes using structure from motion." Earth Surface Dynamics Discussions 3, no. 4 (November 30, 2015): 1345–98. http://dx.doi.org/10.5194/esurfd-3-1345-2015.

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Abstract. Close-range photo-based surface reconstruction from the ground is rapidly emerging as an alternative to lidar (light detection and ranging), which today represents the main survey technique in many fields of geoscience. The recent evolution of photogrammetry, incorporating computer vision algorithms such as Structure from Motion (SfM) and dense image matching such as Multi-View Stereo (MVS), allows the reconstruction of dense 3-D point clouds for the photographed object from a sequence of overlapping images taken with a digital consumer camera. The objective of our work was to test the accuracy of the ground-based SfM-MVS approach in calculating the geodetic mass balance of a 2.1 km2 glacier in the Ortles-Cevedale Group, Eastern Italian Alps. In addition, we investigated the feasibility of using the image-based approach for the detection of the surface displacement rate of a neighbouring active rock glacier. Airborne laser scanning (ALS) data were used as benchmarks to estimate the accuracy of the photogrammetric DTMs and the reliability of the method in this specific application. The glacial and periglacial analyses were performed using both range and image-based surveying techniques, and the results were then compared. The results were encouraging because the SfM-MVS approach enables the reconstruction of high-quality DTMs which provided estimates of glacial and periglacial processes similar to those achievable by ALS. Different resolutions and accuracies were obtained for the glacier and the rock glacier, given the different survey geometries, surface characteristics and areal extents. The analysis of the SfM-MVS DTM quality allowed us to highlight the limitations of the adopted expeditious method in the studied alpine terrain and the potential of this method in the multitemporal study of glacial and periglacial areas.

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Kalacska, Margaret, Oliver Lucanus, J. Pablo Arroyo-Mora, Étienne Laliberté, Kathryn Elmer, George Leblanc, and Andrew Groves. "Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms." Drones 4, no. 2 (April 24, 2020): 13. http://dx.doi.org/10.3390/drones4020013.

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The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.

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Kontogianni, G., R. Chliverou, A. Koutsoudis, G. Pavlidis, and A. Georgopoulos. "INVESTIGATING THE EFFECT OF FOCUS STACKING ON SFM-MVS ALGORITHMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W3 (February 23, 2017): 385–89. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w3-385-2017.

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The Depth of Field (DoF) is a vital factor in photogrammetric applications. Its effect is in most cases pretty obvious especially when capturing small artefacts. It is very important to observe its behaviour as it affects the ability to capture all the details of an object. Focus stacking is a technique in computational photography, in which a set of images focused on different planes with limited DoF are combined in order to considerably extend the DoF. Today, there is a number of focus stacking methods that can be applied in order to produce a full-focus image. In this paper, we investigate the application and effects of focus stacking on SfM-MVS 3D reconstruction. Specifically, our experiment involves the 3D reconstruction of a selected artefact using both traditional all-focus photography and focus stacking. The artefact has already been digitised with a high accuracy and resolution structured light 3D scanner, and that 3D model served as the reference model, with which SfM models were compared. We discuss on these fist results and present some preliminary assessment on the application of focus stacking for the SfM-MVS-based 3D reconstruction.

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David, C. Gabriel, Nina Kohl, Elisa Casella, Alessio Rovere, Pablo Ballesteros, and Torsten Schlurmann. "Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry." Coral Reefs 40, no. 3 (May 3, 2021): 835–51. http://dx.doi.org/10.1007/s00338-021-02088-9.

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AbstractReconstructing the topography of shallow underwater environments using Structure-from-Motion—Multi View Stereo (SfM-MVS) techniques applied to aerial imagery from Unmanned Aerial Vehicles (UAVs) is challenging, as it involves nonlinear distortions caused by water refraction. This study presents an experiment with aerial photographs collected with a consumer-grade UAV on the shallow-water reef of Fuvahmulah, the Maldives. Under conditions of rising tide, we surveyed the same portion of the reef in ten successive flights. For each flight, we used SfM-MVS to reconstruct the Digital Elevation Model (DEM) of the reef and used the flight at low tide (where the reef is almost entirely dry) to compare the performance of DEM reconstruction under increasing water levels. Our results show that differences with the reference DEM increase with increasing depth, but are substantially larger if no underwater ground control points are taken into account in the processing. Correcting our imagery with algorithms that account for refraction did not improve the overall accuracy of reconstruction. We conclude that reconstructing shallow-water reefs (less than 1 m depth) with consumer-grade UAVs and SfM-MVS is possible, but its precision is limited and strongly correlated with water depth. In our case, the best results are achieved when ground control points were placed underwater and no refraction correction is used.

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Moritani, R., S. Kanai, H. Date, Y. Niina, and R. Honma. "QUALITY PREDICTION OF DENSE POINTS GENERATED BY STRUCTURE FROM MOTION FOR HIGH-QUALITY AND EFFICIENT AS-IS MODEL RECONSTRUCTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 95–101. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-95-2019.

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Abstract. In this paper, we introduce a method for predicting the quality of dense points and selecting low-quality regions on the points generated by the structure from motion (SfM) and multi-view stereo (MVS) pipeline to realize high-quality and efficient as-is model reconstruction, using only results from the former: sparse point clouds and camera poses. The method was shown to estimate the quality of the final dense points as the quality predictor on an approximated model obtained from SfM only, without requiring the time-consuming MVS process. Moreover, the predictors can be used for selection of low-quality regions on the approximated model to estimate the next-best optimum camera poses which could improve quality. Furthermore, the method was applied to the prediction of dense point quality generated from the image sets of a concrete bridge column and construction site, and the prediction was validated in a time much shorter than using MVS. Finally, we discussed the correlation between the predictors and the final dense point quality.

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Laburda, Tomáš, Josef Krása, David Zumr, Jan Devátý, Michal Vrána, Nives Zambon, Lisbeth Lolk Johannsen, Andreas Klik, Peter Strauss, and Tomáš Dostál. "SfM‐MVS Photogrammetry for Splash Erosion Monitoring under Natural Rainfall." Earth Surface Processes and Landforms 46, no. 5 (March 8, 2021): 1067–82. http://dx.doi.org/10.1002/esp.5087.

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MURAKI, Hirokazu. "Arrangement when applying SfM/MVS in public surveying using UAV." Journal of the Japan society of photogrammetry and remote sensing 60, no. 3 (2021): 100–103. http://dx.doi.org/10.4287/jsprs.60.100.

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NIINA, Yasuhito, Takuma WAKAIZUMI, and Koji MIZUKAMI. "Introduction of a portable SfM/MVS system “UAV-Map3D (UM3)”." Journal of the Japan society of photogrammetry and remote sensing 60, no. 4 (2021): 177–78. http://dx.doi.org/10.4287/jsprs.60.177.

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HAMA, Akira, Yuka HAYAZAKI, Atsushi MOCHIZUKI, Yasuo TSURUOKA, Kei TANAKA, and Akihiko KONDOH. "Rice Growth Monitoring Using Small UAV and SfM-MVS Technique." JOURNAL OF JAPAN SOCIETY OF HYDROLOGY AND WATER RESOURCES 29, no. 1 (2016): 44–54. http://dx.doi.org/10.3178/jjshwr.29.44.

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Ferreira, Edgar, Jim Chandler, Rene Wackrow, and Koji Shiono. "Automated extraction of free surface topography using SfM-MVS photogrammetry." Flow Measurement and Instrumentation 54 (April 2017): 243–49. http://dx.doi.org/10.1016/j.flowmeasinst.2017.02.001.

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Ioannakis, George, Anestis Koutsoudis, Fotis Arnaoutoglou, Chairi Kiourt, and Christodoulos Chamzas. "On Structure-From-Motion Application Challenges." International Journal of Computational Methods in Heritage Science 1, no. 2 (July 2017): 47–57. http://dx.doi.org/10.4018/ijcmhs.2017070103.

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Numerous software solutions that implement the Structure-from-Motion/Multi-View Stereo (SfM/MVS) 3D reconstruction approach have been made available during the last decade. These allow the production of high quality in terms of geometry and colour information 3D models with the use of unordered image collections that depict a static scene or object from arbitrary viewpoints. Nowadays SfM/MVS-based 3D reconstruction approaches constitute a popular solution in a variety of applications within the cultural heritage domain. As with all 3D reconstruction approaches it has its limitations and application challenges. In this work, the authors attempt to compose a set of guidelines that are based on the important outcomes of important published works that propose solutions that overcome the various challenges introduced by non-friendly surface types.

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Mahami, Hadi, Farnad Nasirzadeh, Ali Hosseininaveh Ahmadabadian, and Saeid Nahavandi. "Automated Progress Controlling and Monitoring Using Daily Site Images and Building Information Modelling." Buildings 9, no. 3 (March 20, 2019): 70. http://dx.doi.org/10.3390/buildings9030070.

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This research presents a novel method for automated construction progress monitoring. Using the proposed method, an accurate and complete 3D point cloud is generated for automatic outdoor and indoor progress monitoring throughout the project duration. In this method, Structured-from-Motion (SFM) and Multi-View-Stereo (MVS) algorithms coupled with photogrammetric principles for the coded targets’ detection are exploited to generate as-built 3D point clouds. The coded targets are utilized to automatically resolve the scale and increase the accuracy of the point cloud generated using SFM and MVS methods. Having generated the point cloud, the CAD model is generated from the as-built point cloud and compared with the as-planned model. Finally, the quantity of the performed work is determined in two real case study projects. The proposed method is compared to the Structured-from-Motion (SFM)/Clustering Multi-Views Stereo (CMVS)/Patch-based Multi-View Stereo (PMVS) algorithm, as a common method for generating 3D point cloud models. The proposed photogrammetric Multi-View Stereo method reveals an accuracy of around 99 percent and the generated noises are less compared to the SFM/CMVS/PMVS algorithm. It is observed that the proposed method has extensively improved the accuracy of generated points cloud compared to the SFM/CMVS/PMVS algorithm. It is believed that the proposed method may present a novel and robust tool for automated progress monitoring in construction projects.

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Fuse, T., and H. Ikezawa. "DEVELOPMENT OF MULTI-VIEW STEREO CONSIDERING ACCURACY OF EXTERIOR ORIENTATION ELEMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W18 (November 29, 2019): 47–52. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w18-47-2019.

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Abstract. Structure from motion (SfM) has been widely used to achieve automatic 3D reconstructions. However, as the 3D point clouds obtained via SfM are sparse, multi-view stereo (MVS) was developed to compensate for this sparseness. The accuracy of the 3D surface depends on the accuracy of the orientation elements based on the SfM. Additionally, in the case of an unmanned aerial vehicle (UAV), SfM exhibits a decrease in the accuracy of the orientation elements during complex camera movements. This paper proposes a patch-based MVS (PMVS) method considering the accuracy of the orientation elements. The proposed method involves applying the global SfM, estimating accuracy of exterior orientation (EO) elements, and introducing the accuracy of EO elements to PMVS. The PMVS approximates an object surface by using small rectangular patches, namely local tangent plane approximation. The patches are optimized by minimizing the sum of the photometric discrepancy scores. The accuracy of the EO elements is introduced to the patch optimization as weighting function. This accuracy is defined using the variances of the estimated parameters in the bundle adjustment. We also investigate the types of weighting functions. The results indicate that the proposed method is capable of considering geometric conditions during patch estimation. The proposed method was applied to the three types of image datasets, i.e., images captured using an SLR camera at ground level, images captured using a UAV equipped with a SLR camera, and images captured using an airplane equipped with an oblique camera. Through the experimental results, the improved accuracy and the effectiveness of the proposed method were confirmed.

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Marín-Comitre, Ubaldo, Álvaro Gómez-Gutiérrez, Francisco Lavado-Contador, Manuel Sánchez-Fernández, and Alberto Alfonso-Torreño. "Using Geomatic Techniques to Estimate Volume–Area Relationships of Watering Ponds." ISPRS International Journal of Geo-Information 10, no. 8 (July 26, 2021): 502. http://dx.doi.org/10.3390/ijgi10080502.

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Watering ponds represent an important part of the hydrological resources in some water-limited environments. Knowledge about their storage capacity and geometrical characteristics is crucial for a better understanding and management of water resources in the context of climate change. In this study, the suitability of different geomatic approaches to model watering pond geometry and estimate pond-specific and generalized volume–area–height (V–A–h) relationships was tested. Terrestrial structure-from-motion and multi-view-stereo photogrammetry (SfM-MVS), terrestrial laser scanner (TLS), laser-imaging detection and ranging (LIDAR), and aerial SfM-MVS were tested for the emerged terrain, while the global navigation satellite system (GNSS) was used to survey the submerged terrain and to test the resulting digital elevation models (DEMs). The combined use of terrestrial SfM-MVS and GNSS produced accurate DEMs of the ponds that resulted in an average error of 1.19% in the maximum volume estimation, comparable to that obtained by the TLS+GNSS approach (3.27%). From these DEMs, power and quadratic functions were used to express pond-specific and generalized V–A–h relationships and checked for accuracy. The results revealed that quadratic functions fit the data particularly well (R2 ≥ 0.995 and NRMSE < 2.25%) and can therefore be reliably used as simple geometric models of watering ponds in hydrological simulation studies. Finally, a generalized V–A power relationship was obtained. This relationship may be a valuable tool to estimate the storage capacity of other watering ponds in comparable areas in a context of data scarcity.

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Hayakawa, Yuichi S., and Hiroyuki Obanawa. "Aerial measurements of topography using small UAS and SfM-MVS photogrammetry." BUTSURI-TANSA(Geophysical Exploration) 69, no. 4 (2016): 297–309. http://dx.doi.org/10.3124/segj.69.297.

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若泉, 拓磨, 恭仁新名, and 幸治水上. "可搬型SfM/MVSシステム「UAV-Map3D」の開発." Journal of the Japan society of photogrammetry and remote sensing 59, no. 3 (2020): 102–3. http://dx.doi.org/10.4287/jsprs.59.102.

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Nakano, T., I. Kamiya, M. Tobita, J. Iwahashi, and H. Nakajima. "Landform monitoring in active volcano by UAV and SfM-MVS technique." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 27, 2014): 71–75. http://dx.doi.org/10.5194/isprsarchives-xl-8-71-2014.

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Nishinoshima volcano in Ogasawara Islands has erupted since November, 2013. This volcanic eruption formed and enlarged a new island, and fused the new island with the old Nishinoshima Island. We performed automated aerial photographing using an Unmanned Aerial Vehicle (UAV) over the joined Nishinoshima Island on March 22 and July 4, 2014. We produced ortho-mosaic photos and digital elevation model (DEM) data by new photogrammetry software with computer vision technique, i.e. Structure from Motion (SfM) for estimating the photographic position of the camera and Multi-view Stereo (MVS) for generating the 3-D model. We also estimated the area and volume of the new island via analysis of ortho-mosaic photo and DEM data. Transition of volume estimated from the UAV photographing and other photographing shows the volcanic activity still keeps from initial level. The ortho-mosaic photos and DEM data were utilized to create an aerial photo interpretation map and a 3-D map. These operations revealed new knowledge and problems to be solved on the photographing and analysis using UAV and new techniques as this was first case in some respects.

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Agrafiotis, P., G. I. Drakonakis, A. Georgopoulos, and D. Skarlatos. "THE EFFECT OF UNDERWATER IMAGERY RADIOMETRY ON 3D RECONSTRUCTION AND ORTHOIMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W3 (February 23, 2017): 25–31. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w3-25-2017.

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The work presented in this paper investigates the effect of the radiometry of the underwater imagery on automating the 3D reconstruction and the produced orthoimagery. Main aim is to investigate whether pre-processing of the underwater imagery improves the 3D reconstruction using automated SfM - MVS software or not. Since the processing of images either separately or in batch is a time-consuming procedure, it is critical to determine the necessity of implementing colour correction and enhancement before the SfM - MVS procedure or directly to the final orthoimage when the orthoimagery is the deliverable. Two different test sites were used to capture imagery ensuring different environmental conditions, depth and complexity. Three different image correction methods are applied: A very simple automated method using Adobe Photoshop, a developed colour correction algorithm using the CLAHE (Zuiderveld, 1994) method and an implementation of the algorithm described in Bianco et al., (2015). The produced point clouds using the initial and the corrected imagery are then being compared and evaluated.

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Zainuddin, K., Z. Majid, M. F. M. Ariff, and K. M. Idris. "MEASUREMENT ACCURACY ON 3D POINT CLOUD GENERATED USING MULTISPECTRAL IMAGERY BY DIFFERENT CALIBRATION METHODS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 697–703. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-697-2019.

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Abstract. The state-of-the-art lightweight multispectral cameras are widely used for low altitude remote sensing, also can be exploited as a tool for close-range photogrammetry application. The acquired imagery can be used for generating the 3D model using Structure-from-Motion/ Multi-view Stereo (SfM/MVS) processing software. In photogrammetry, camera calibration is an essential step for accurate measurement. The parameter of the camera system can be estimated using photogrammetric self-calibration bundle-adjustment, or by automatic and straightforward calibration procedure developed by computer vision (CV) community. When using SfM/MVS photogrammetry software, the pre-calibration value is not required, as the algorithm calculates the parameter as a part of point cloud construction process. Nevertheless, processing with the uncalibrated image is only suitable when no metric accuracy required in the modelling project. This paper aims to evaluate the measurement accuracy on generated 3D point cloud based on different estimated parameter method. The evaluation of measurement accuracy started by estimates the camera’s interior parameter using two different approaches; photogrammetric self-calibration bundle-adjustment and computer vision calibration. The estimated parameter from both methods then imported into commercial SfM/MVS software to construct the 3D point cloud. The point cloud also generated using uncalibrated images and used for measurement accuracy assessment. All parameters applied to the same datasets involved three different check-fields. Two accuracy assessments were performed by comparing the check-points and check-distance extracted with the total station measurement. As a result, the point cloud generated using photogrammetric approach provides the most accurate result on both assessments. While the automatic on-the-job self-calibration shows inconsistent results.

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Gao, Lei, Yingbao Zhao, Jingchang Han, and Huixian Liu. "Research on Multi-View 3D Reconstruction Technology Based on SFM." Sensors 22, no. 12 (June 9, 2022): 4366. http://dx.doi.org/10.3390/s22124366.

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Multi-view 3D reconstruction technology is used to restore a 3D model of practical value or required objects from a group of images. This paper designs and implements a set of multi-view 3D reconstruction technology, adopts the fusion method of SIFT and SURF feature-point extraction results, increases the number of feature points, adds proportional constraints to improve the robustness of feature-point matching, and uses RANSAC to eliminate false matching. In the sparse reconstruction stage, the traditional incremental SFM algorithm takes a long time, but the accuracy is high; the traditional global SFM algorithm is fast, but its accuracy is low; aiming at the disadvantages of traditional SFM algorithm, this paper proposes a hybrid SFM algorithm, which avoids the problem of the long time consumption of incremental SFM and the problem of the low precision and poor robustness of global SFM; finally, the MVS algorithm of depth-map fusion is used to complete the dense reconstruction of objects, and the related algorithms are used to complete the surface reconstruction, which makes the reconstruction model more realistic.

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Chudley, Thomas R., Poul Christoffersen, Samuel H. Doyle, Antonio Abellan, and Neal Snooke. "High-accuracy UAV photogrammetry of ice sheet dynamics with no ground control." Cryosphere 13, no. 3 (March 19, 2019): 955–68. http://dx.doi.org/10.5194/tc-13-955-2019.

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Abstract. Unmanned aerial vehicles (UAVs) and structure from motion with multi-view stereo (SfM–MVS) photogrammetry are increasingly common tools for geoscience applications, but final product accuracy can be significantly diminished in the absence of a dense and well-distributed network of ground control points (GCPs). This is problematic in inaccessible or hazardous field environments, including highly crevassed glaciers, where implementing suitable GCP networks would be logistically difficult if not impossible. To overcome this challenge, we present an alternative geolocation approach known as GNSS-supported aerial triangulation (GNSS-AT). Here, an on-board carrier-phase GNSS receiver is used to determine the location of photo acquisitions using kinematic differential carrier-phase positioning. The camera positions can be used as the geospatial input to the photogrammetry process. We describe the implementation of this method in a low-cost, custom-built UAV and apply the method in a glaciological setting at Store Glacier in western Greenland. We validate the technique at the calving front, achieving topographic uncertainties of ±0.12 m horizontally (∼1.1× the ground sampling distance) and ±0.14 m vertically (∼1.3× the ground sampling distance), when flying at an altitude of ∼ 450 m above ground level. This compares favourably with previous GCP-derived uncertainties in glacial environments and allows us to apply the SfM–MVS photogrammetry at an inland study site where ice flows at 2 m day−1 and stable ground control is not available. Here, we were able to produce, without the use of GCPs, the first UAV-derived velocity fields of an ice sheet interior. Given the growing use of UAVs and SfM–MVS in glaciology and the geosciences, GNSS-AT will be of interest to those wishing to use UAV photogrammetry to obtain high-precision measurements of topographic change in contexts where GCP collection is logistically constrained.

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Agrafiotis, P., D. Skarlatos, A. Georgopoulos, and K. Karantzalos. "SHALLOW WATER BATHYMETRY MAPPING FROM UAV IMAGERY BASED ON MACHINE LEARNING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W10 (April 17, 2019): 9–16. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w10-9-2019.

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Abstract. The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological mapping and biological research. UAV imagery processed with Structure from Motion (SfM) and Multi View Stereo (MVS) techniques can provide a low-cost alternative to established shallow seabed mapping techniques offering as well the important visual information. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this paper, in order to overcome the water refraction errors, we employ machine learning tools that are able to learn the systematic underestimation of the estimated depths. In the proposed approach, based on known depth observations from bathymetric LiDAR surveys, an SVR model was developed able to estimate more accurately the real depths of point clouds derived from SfM-MVS procedures. Experimental results over two test sites along with the performed quantitative validation indicated the high potential of the developed approach.

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Vlachos, M., A. Calantropio, D. Skarlatos, and F. Chiabrando. "MODELLING COLOUR ABSORPTION OF UNDERWATER IMAGES USING SFM-MVS GENERATED DEPTH MAPS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2022 (May 30, 2022): 959–66. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2022-959-2022.

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Abstract. The problem of colour correction of underwater images concerns not only surveyors, who primarily use images for photogrammetric purposes, but also archaeologists, marine biologists, and many other domains experts whose aim is to study objects and lifeforms underwater. Different methods exist in the literature; some of them provide outstanding results but works involving physical models that take into account additional information and variables (light conditions, depths, camera to objects distances, water properties) that are not always available or can be measured using expensive equipment or calculated using more complicated models. Some other methods have the advantages of working with basically all kinds of dataset, but without considering any geometric information, therefore applying corrections that work only in very generic conditions that most of the time differs from the real-world applications.This paper presents an easy and fast method for restoring the colour information on images captured underwater. The compelling idea is to model light backscattering and absorption variation according to the distance of the surveyed object. This information is always obtainable in photogrammetric datasets, as the model utilises the scene's 3D geometry by creating and using SfM-MVS generated depth maps, which are crucial for implementing the proposed methodology. The results presented visually and quantitatively are promising since they are an excellent compromise to provide a straightforward and easily adaptable workflow to restore the colour information in underwater images.

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TAKAHASHI, Yoji. "The comparison of 3D reconstruction by SfM/MVS for various GCPs arrangement." Journal of the Japan society of photogrammetry and remote sensing 60, no. 4 (2021): 179–82. http://dx.doi.org/10.4287/jsprs.60.179.

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CHO, Yonghwan, Ryoya NAKAYAMA, Masami KIKU, Tomoaki NAKAMURA, and Norimi MIZUTANI. "BEACH DEFORMATION ANALYSIS BY COMBINING NETWORK CAMERA AND UAV-SFM/MVS SURVEY." Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering) 76, no. 2 (2020): I_655—I_660. http://dx.doi.org/10.2208/kaigan.76.2_i_655.

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Moyano, Juan, Juan E. Nieto-Julián, Daniel Antón, Elena Cabrera, David Bienvenido-Huertas, and Nazareth Sánchez. "Suitability Study of Structure-from-Motion for the Digitisation of Architectural (Heritage) Spaces to Apply Divergent Photograph Collection." Symmetry 12, no. 12 (November 30, 2020): 1981. http://dx.doi.org/10.3390/sym12121981.

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The digitisation of architectural heritage has experienced a great development of low-cost and high-definition data capture technologies, thus enabling the accurate and effective modelling of complex heritage assets. Accordingly, research has identified the best methods to survey historic buildings, but the suitability of Structure-from-Motion/Multi-view-Stereo (SfM/MVS) for interior square symmetrical architectural spaces is unexplored. In contrast to the traditional SfM surveying for which the camera surrounds the object, the photograph collection approach is divergent in courtyards. This paper evaluates the accuracy of SfM point clouds against Terrestrial Laser Scanning (TLS) for these large architectural spaces with a symmetrical configuration, with the main courtyard of Casa de Pilatos in Seville, Spain, as a case study. Two different SfM surveys were conducted: (1) Without control points, and (2) referenced using a total station. The first survey yielded unacceptable results: A standard deviation of 0.0576 m was achieved in the northwest sector of the case study, mainly because of the difficulty of aligning the SfM and TLS data due to the way they are produced. This value could be admissible depending on the purpose of the photogrammetric model.

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Romero-Chambi, Eduardo, Simón Villarroel-Quezada, Edison Atencio, and Felipe Muñoz-La Rivera. "Analysis of Optimal Flight Parameters of Unmanned Aerial Vehicles (UAVs) for Detecting Potholes in Pavements." Applied Sciences 10, no. 12 (June 17, 2020): 4157. http://dx.doi.org/10.3390/app10124157.

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Pavement maintenance seeks to provide optimal service conditions. Before maintenance, it is necessary to know the condition of the pavement by inspection, a crucial step in deciding on the repair to be carried out. In this sense, unmanned aerial vehicles (UAVs) seem to be an economic substitute compared to the ground laser scanner for pavement inspection tasks. This research seeks to develop a method to measure potholes using 3D models generated with photographs acquired by a UAV and process them using a software based on the Structure from Motion-MultiView Stereo (SfM–MVS) technique. The contribution of this document is the proposal of recommendations for the acquisition of photographs for the realization of the models. To develop these recommendations, an experiment was carried out to evaluate the accuracy in the reconstruction of 3D models using images obtained from the variation and combination of flight planning parameters and data capture. Then, to validate these recommendations, a bumpy section of pavement was modeled using the SfM–MVS method. The results show that for heights of 10 and 15 m the use of this methodology is applicable for the measurement of the width and depth of potholes.

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Pepe, Massimiliano, Vincenzo Saverio Alfio, and Domenica Costantino. "UAV Platforms and the SfM-MVS Approach in the 3D Surveys and Modelling: A Review in the Cultural Heritage Field." Applied Sciences 12, no. 24 (December 15, 2022): 12886. http://dx.doi.org/10.3390/app122412886.

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In recent years, structure from motion (SfM) and multi-view stereo (MVS) algorithms have been successfully applied to stereo images generated by cameras mounted on unmanned aerial vehicle (UAV) platforms to build 3D models. Indeed, the approach based on the combination of SfM-MVS and UAV-generated images allows for cost-effective acquisition, fast and automated processing, and detailed and accurate reconstruction of 3D models. As a consequence, this approach has become very popular for representation, management, and conservation in the field of cultural heritage (CH). Therefore, this review paper discusses the use of UAV photogrammetry in CH environments with a focus on state of the art trends and best practices in image acquisition technologies and 3D model-building software. In particular, this paper intends to emphasise the different techniques of image acquisition and processing in relation to the different platforms and navigation systems available, as well as to analyse and deepen the aspects of 3D reconstruction that efficiently describe the entire photogrammetric process, providing further insights for new applications in different fields, such as structural engineering and conservation and maintenance restoration of sites and structures belonging to the CH field.

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Vinatier, Fabrice, Jeanne Dollinger, Gabrielle Rudi, Denis Feurer, Gilles Belaud, and Jean-Stéphane Bailly. "The Use of Photogrammetry to Construct Time Series of Vegetation Permeability to Water and Seed Transport in Agricultural Waterways." Remote Sensing 10, no. 12 (December 17, 2018): 2050. http://dx.doi.org/10.3390/rs10122050.

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Terrestrial vegetation has numerous positive effects on the main regulating services of agricultural channels, such as seed retention, pollutant mitigation, bank stabilization, and sedimentation, and this vegetation acts as a porous medium for the flow of matter through the channels. This vegetation also limits the water conveyance in channels, and consequently is frequently removed by farmers to increase its porosity. However, the temporal effects of these management practices remain poorly understood. Indeed, the vegetation porosity exhibits important temporal variations according to the maintenance schedule, and the water level also varies with time inside a given channel section according to rainfall events or irrigation practices. To maximise the impacts of vegetation on agricultural channels, it is now of primary importance to measure vegetation porosity according to water level over a long time period rather than at a particular time. Time series of such complex vegetation characteristics have never been studied using remote sensing methods. Here, we present a new approach using the Structure-from-Motion approach using a Multi-View Stereo algorithm (SfM-MVS) technique to construct time series of herbaceous vegetation porosity in a real agricultural channel managed by five different practices: control, dredging, mowing, burning, and chemical weeding. We post-processed the time series of point clouds to create an indicator of vegetation porosity for the whole section and of the surface of the channel. Mowing and chemical weeding are the practices presenting the most favorable temporal evolutions of the porosity indicators regarding flow events. Burning did not succeed in restoring the porosity of the channel due to quick recovery of the vegetation and dephasing of the maintenance calendar with the flow events. The high robustness of the technique and the automatization of the SfM-MVS calculation together with the post-processing of the point clouds should help in handling time series of SfM-MVS data for applications in ecohydrology or agroecology.

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Parente, Luigi, Jim H. Chandler, and Neil Dixon. "Automated Registration of SfM‐MVS Multitemporal Datasets Using Terrestrial and Oblique Aerial Images." Photogrammetric Record 36, no. 173 (January 6, 2021): 12–35. http://dx.doi.org/10.1111/phor.12346.

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KITADA, Yuhei, Yoshihiro YASUMURO, Hiroshige DAN, Ryosuke MATSUSHITA, and Tatsuaki NISHIGATA. "Optimization Scenario for Large Scale 3D-Scanning Plans based on SFM and MVS." Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 71, no. 2 (2015): I_169—I_175. http://dx.doi.org/10.2208/jscejcei.71.i_169.

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Hanbudi, Giri, and Esa Fauzi. "Rekonstruksi Model 3D dari Set Citra Menggunakan Metode SFM-MVS dan Algoritma Poisson." JURNAL MEDIA INFORMATIKA BUDIDARMA 6, no. 3 (July 25, 2022): 1304. http://dx.doi.org/10.30865/mib.v6i3.4126.

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The digital creative industry is growing massively and very fast. The use of 3D technology in various industrial fields is also in demand, for example in the manufacturing, film, and animation industries. In a certain scene, generally 3D generalists will create a 3D model that resembles a real model in the real world which is usually used as a property in the 3D scene such as accessories, furniture, wardrobes, and so on. The process of modeling 3D models manually by a 3D generalist is a long process and requires a long time in the process, where the process generally includes 3d layouting, 3d modeling, and 3d texturing. Through this 3D model reconstruction process, 3D models can be obtained quickly, cheaply, and efficiently. This process can be carried out through several stages using a set of images from a model to be reconstructed. Several approaches can be used in this 3D model reconstruction process. In this paper, we will use the Structure From Motion (SFM) and Multi-View Stereo (MVS) methods to obtain information on the sparse and dense point clouds in the image, followed by The Surface Reconstruction process using the Poisson Algorithm to obtain a triangle mesh from the actual shape of the object. The refinement process on the triangle mesh results is carried out in order to get maximum results. Through a combination of these methods, we managed to get a detailed and accurate 3D model with the real object being observed.

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Parente, Luigi, Jim H. Chandler, and Neil Dixon. "Optimising the quality of an SfM‐MVS slope monitoring system using fixed cameras." Photogrammetric Record 34, no. 168 (September 12, 2019): 408–27. http://dx.doi.org/10.1111/phor.12288.

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Agrafiotis, Panagiotis, Dimitrios Skarlatos, Andreas Georgopoulos, and Konstantinos Karantzalos. "DepthLearn: Learning to Correct the Refraction on Point Clouds Derived from Aerial Imagery for Accurate Dense Shallow Water Bathymetry Based on SVMs-Fusion with LiDAR Point Clouds." Remote Sensing 11, no. 19 (September 24, 2019): 2225. http://dx.doi.org/10.3390/rs11192225.

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The determination of accurate bathymetric information is a key element for near offshore activities; hydrological studies, such as coastal engineering applications, sedimentary processes, hydrographic surveying, archaeological mapping and biological research. Through structure from motion (SfM) and multi-view-stereo (MVS) techniques, aerial imagery can provide a low-cost alternative compared to bathymetric LiDAR (Light Detection and Ranging) surveys, as it offers additional important visual information and higher spatial resolution. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this article, in order to overcome the water refraction errors in a massive and accurate way, we employ machine learning tools, which are able to learn the systematic underestimation of the estimated depths. In particular, an SVR (support vector regression) model was developed, based on known depth observations from bathymetric LiDAR surveys, which is able to accurately recover bathymetry from point clouds derived from SfM-MVS procedures. Experimental results and validation were based on datasets derived from different test-sites, and demonstrated the high potential of our approach. Moreover, we exploited the fusion of LiDAR and image-based point clouds towards addressing challenges of both modalities in problematic areas.

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MALLALIEU, JOSEPH, JONATHAN L. CARRIVICK, DUNCAN J. QUINCEY, MARK W. SMITH, and WILLIAM H. M. JAMES. "An integrated Structure-from-Motion and time-lapse technique for quantifying ice-margin dynamics." Journal of Glaciology 63, no. 242 (October 9, 2017): 937–49. http://dx.doi.org/10.1017/jog.2017.48.

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ABSTRACTFine resolution topographic data derived from methods such as Structure from Motion (SfM) and Multi-View Stereo (MVS) have the potential to provide detailed observations of geomorphological change, but have thus far been limited by the logistical constraints of conducting repeat surveys in the field. Here, we present the results from an automated time-lapse camera array, deployed around an ice-marginal lake on the western margin of the Greenland ice sheet. Fifteen cameras acquired imagery three-times per day over a 426 day period, yielding a dataset of ~19 000 images. From these data we derived 18 point clouds of the ice-margin across a range of seasons and successfully identified calving events (ranging from 234 to 1475 m2 in area and 815–8725 m3 in volume) induced by ice cliff undercutting at the waterline and the collapse of spalling flakes. Low ambient light levels, locally reflective surfaces and the large survey range hindered analysis of smaller scale ice-margin dynamics. Nevertheless, this study demonstrates that an integrated SfM-MVS and time-lapse approach can be employed to generate long-term 3-D topographic datasets and thus quantify ice-margin dynamics at a fine spatio-temporal scale. This approach provides a template for future studies of geomorphological change.

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Jasińska, Aleksandra, Krystian Pyka, Elżbieta Pastucha, and Henrik Skov Midtiby. "A Simple Way to Reduce 3D Model Deformation in Smartphone Photogrammetry." Sensors 23, no. 2 (January 9, 2023): 728. http://dx.doi.org/10.3390/s23020728.

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Recently, the term smartphone photogrammetry gained popularity. This suggests that photogrammetry may become a simple measurement tool by virtually every smartphone user. The research was undertaken to clarify whether it is appropriate to use the Structure from Motion—Multi Stereo View (SfM-MVS) procedure with self-calibration as it is done in Uncrewed Aerial Vehicle photogrammetry. First, the geometric stability of smartphone cameras was tested. Fourteen smartphones were calibrated on the checkerboard test field. The process was repeated multiple times. These observations were found: (1) most smartphone cameras have lower stability of the internal orientation parameters than a Digital Single-Lens Reflex (DSLR) camera, and (2) the principal distance and position of the principal point are constantly changing. Then, based on images from two selected smartphones, 3D models of a small sculpture were developed. The SfM-MVS method was used, with self-calibration and pre-calibration variants. By comparing the resultant models with the reference DSLR-created model it was shown that introducing calibration obtained in the test field instead of self-calibration improves the geometry of 3D models. In particular, deformations of local concavities and convexities decreased. In conclusion, there is real potential in smartphone photogrammetry, but it also has its limits.

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Zhang, Yuxin, Lei Zhang, Guochen Shen, and Qian Xu. "Physical Structure Expression for Dense Point Clouds of Magnetic Levitation Image Data." Sensors 23, no. 5 (February 24, 2023): 2535. http://dx.doi.org/10.3390/s23052535.

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The research and development of an intelligent magnetic levitation transportation system has become an important research branch of the current intelligent transportation system (ITS), which can provide technical support for state-of-the-art fields such as intelligent magnetic levitation digital twin. First, we applied unmanned aerial vehicle oblique photography technology to acquire the magnetic levitation track image data and preprocessed them. Then, we extracted the image features and matched them based on the incremental structure from motion (SFM) algorithm, recovered the camera pose parameters of the image data and the 3D scene structure information of key points, and optimized the bundle adjustment to output 3D magnetic levitation sparse point clouds. Then, we applied multiview stereo (MVS) vision technology to estimate the depth map and normal map information. Finally, we extracted the output of the dense point clouds that can precisely express the physical structure of the magnetic levitation track, such as turnout, turning, linear structures, etc. By comparing the dense point clouds model with the traditional building information model, experiments verified that the magnetic levitation image 3D reconstruction system based on the incremental SFM and MVS algorithm has strong robustness and accuracy and can express a variety of physical structures of magnetic levitation track with high accuracy.

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Godfrey, Samantha, James R. Cooper, and Andrew J. Plater. "Roving Multiple Camera Array with Structure-from-Motion for Coastal Monitoring." Journal of Marine Science and Engineering 11, no. 3 (March 10, 2023): 591. http://dx.doi.org/10.3390/jmse11030591.

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Regular monitoring is essential for vulnerable coastal locations such as areas of landward retreat. However, for coastal practitioners, surveying is limited by budget, specialist personnel/equipment and weather. In combination structure-from-motion and multi-view stereo (SfM-MVS) has helped to improve accessibility to topographic data acquisition. Pole-mounted cameras with SfM-MVS have gained traction but to guarantee coverage and reconstruction quality, greater understanding of camera position and interaction is required. This study uses a multi-camera array for image acquisition and reviews processing procedures in Agisoft Photoscan (Metashape). The camera rig was deployed at three sites and results were verified against a terrestrial laser scanner (TLS) and independent precision estimates. The multi-camera approach provided effective image acquisition ~11 times faster than the TLS. Reconstruction quality equalled (>92% similarity) the TLS, subject to processing parameters. A change in the image alignment parameter demonstrated a significant influence on deformation, reducing reprojection error by~94%. A lower densification parameter (‘High’) offered results ~4.39% dissimilar from the TLS at 1/8th of the processing time of other parameters. Independent precision estimates were <8.2 mm for x, y and z dimensions. These findings illustrate the potential of multi-camera systems and the influence of processing on point cloud quality and computation time.

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Lane, Stuart N., Alice Gentile, and Lucien Goldenschue. "Combining UAV-Based SfM-MVS Photogrammetry with Conventional Monitoring to Set Environmental Flows: Modifying Dam Flushing Flows to Improve Alpine Stream Habitat." Remote Sensing 12, no. 23 (November 25, 2020): 3868. http://dx.doi.org/10.3390/rs12233868.

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Setting environmental flows downstream of hydropower dams is widely recognized as important, particularly in Alpine regions. However, the required flows are strongly influenced by the effects of the physical environment of the downstream river. Here, we show how unmanned aerial vehicle (UAV)-based structure-from-motion multiview stereo (SfM-MVS) photogrammetry allows for incorporation of such effects through determination of spatially distributed patterns of key physical parameters (e.g., bed shear stress, bed grain size) and how they condition available stream habitat. This is illustrated for a dam-impacted Alpine stream, testing whether modification of the dam’s annual flushing flow could achieve the desired downstream environmental improvement. In detail, we found that (1) flood peaks in the pilot study were larger than needed, (2) only a single flood peak was necessary, (3) sediment coarsening was likely being impacted by supply from nonregulated tributaries, often overlooked, and (4) a lower-magnitude but longer-duration rinsing flow after flushing is valuable for the system. These findings were enabled by the spatially rich geospatial datasets produced by UAV-based SfM-MVS photogrammetry. Both modeling of river erosion and deposition and river habitat may be revolutionized by these developments in remote sensing. However, it is combination with more traditional and temporarily rich monitoring that allows their full potential to be realized.

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Kochi, Nobuo, Sachiko Isobe, Atsushi Hayashi, Kunihiro Kodama, and Takanari Tanabata. "Introduction of All-Around 3D Modeling Methods for Investigation of Plants." International Journal of Automation Technology 15, no. 3 (May 5, 2021): 301–12. http://dx.doi.org/10.20965/ijat.2021.p0301.

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Digital image phenotyping has become popular in plant research. Plants are complex in shape, and occlusion can often occur. Three-dimensional (3D) data are expected to measure the morphological traits of plants with higher accuracy. Plants have organs with flat and/or narrow shapes and similar component structures are repeated. Therefore, it is difficult to construct an accurate 3D model by applying methods developed for industrial materials and architecture. Here, we review noncontact and all-around 3D modeling and configuration of camera systems to measure the morphological traits of plants in terms of system composition, accuracy, cost, and usability. Typical noncontact 3D measurement methods can be roughly classified into active and passive methods. We describe their advantages and disadvantages. Structure-from-motion/multi-view stereo (SfM/MVS), a passive method, is the most frequently used measurement method for plants. It is described in terms of “forward intersection” and “backward resection.” We recently developed a novel SfM/MVS approach by mixing the forward and backward methods, and we provide a brief overview of our approach in this paper. While various fields are adopting 3D model construction, nonexpert users struggle to use them and end up selecting inadequate methods, which lead to model failure. We hope that this review will help users who are considering starting to construct and measure 3D models.

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Nakano, Takayuki, Hiroshi Une, Kazuki Yoshida, Satoshi Fujiwara, and Tomokazu Kobayashi. "Evaluating earthquake-related ground failure mapping by combined traditional and modern methods." Advances in Cartography and GIScience of the ICA 1 (July 3, 2019): 1–8. http://dx.doi.org/10.5194/ica-adv-1-14-2019.

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Abstract. A wide range of ground failure such as earthquake faulting (surface rupture), landslides, and liquefaction occur after a large earthquake. In this study, in order to rapidly determine the distribution of failure over a wide area after an earthquake, we combined traditional methods such as aerial photo interpretation and modern methods such as unmanned aerial vehicle (UAV) or interferometric synthetic aperture radar (InSAR) techniques. Moreover, elevation variations obtained using DEMs and the structure from motion and multi-view stereo (SfM-MVS) technique were employed to understand local ground deformation factors, such as reclaimed valley deformation. Using ortho-mosaic images, surface fissures caused by the 2016 Kumamoto Earthquake in Japan were rapidly interpreted and mapped, which enabled early interpretation of the ground failure situation. Furthermore, surface displacement properties extracted from SAR interferograms allowed for more advanced earthquake fault detection; surface displacement associated with liquefaction was also identified from SAR interferograms. In addition, InSAR was used to detect reclaimed valley deformation. Comparing this with the reclaimed valley distribution map created by the SfM-MVS technique improved our understanding of this phenomenon. However, many of these techniques require large amounts of manpower and time and can be influenced by differences in analyst skill level. In future, the development of mechanically automated ground failure identification will improve earthquake disaster responses.

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Journal articles on the topic 'SfM-MVS'

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