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Relevant bibliographies by topics / Kinematic identification- Vision based techniques

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Academic literature on the topic 'Kinematic identification- Vision based techniques'

Author: Grafiati

Published: 6 September 2023

Last updated: 31 July 2025

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Journal articles on the topic "Kinematic identification- Vision based techniques"

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Seah, Shao Xuan, Yan Han Lau, and Sutthiphong Srigrarom. "Multiple Aerial Targets Re-Identification by 2D- and 3D- Kinematics-Based Matching." Journal of Imaging 8, no. 2 (2022): 26. http://dx.doi.org/10.3390/jimaging8020026.

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This paper presents two techniques in the matching and re-identification of multiple aerial target detections from multiple electro-optical devices: 2-dimensional and 3-dimensional kinematics-based matching. The main advantage of these methods over traditional image-based methods is that no prior image-based training is required; instead, relatively simpler graph matching algorithms are used. The first 2-dimensional method relies solely on the kinematic and geometric projections of the detected targets onto the images captured by the various cameras. Matching and re-identification across frame

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Chen, Biao, Chaoyang Chen, Jie Hu, et al. "Computer Vision and Machine Learning-Based Gait Pattern Recognition for Flat Fall Prediction." Sensors 22, no. 20 (2022): 7960. http://dx.doi.org/10.3390/s22207960.

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Background: Gait recognition has been applied in the prediction of the probability of elderly flat ground fall, functional evaluation during rehabilitation, and the training of patients with lower extremity motor dysfunction. Gait distinguishing between seemingly similar kinematic patterns associated with different pathological entities is a challenge for the clinician. How to realize automatic identification and judgment of abnormal gait is a significant challenge in clinical practice. The long-term goal of our study is to develop a gait recognition computer vision system using artificial int

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Huang, Jianbing, and Chia-Hsiang Menq. "Identification and Characterization of Regular Surfaces from Unorganized Points by Normal Sensitivity Analysis." Journal of Computing and Information Science in Engineering 2, no. 2 (2002): 115–24. http://dx.doi.org/10.1115/1.1509075.

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In this paper, the concept of free motion subspace is introduced and utilized to characterize the special kinematic properties of regular surfaces, including planes, natural quadrics, and regular swept surfaces. Based on the concept, a general approach is developed to automatically identify the surface type and calculate the associated geometric parameters of an unknown surface from unorganized measurement points. In the approach, a normal sensitivity matrix, that characterizes the normal perturbation of surface points under differential motions, is derived. With the normal sensitivity matrix,

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Amami, Mustafa M. "Fast and Reliable Vision-Based Navigation for Real Time Kinematic Applications." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (2022): 922–32. http://dx.doi.org/10.22214/ijraset.2022.40395.

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Abstract: Automatic Image Matching (AIM) is the term used to identify the automatic detection of corresponding points located on the overlapping areas of multiple images. AIM is extensively used with Mobile Mapping System (MMS) for different engineering applications, such as highway infrastructure mapping, monitoring of road surface quality and markings, telecommunication, emergency response, and collecting data for Geographical Information Systems (GIS). Robotics community and Simultaneous Localization And Mapping (SLAM) based applications are other important areas that require fact and welld

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Wei, Hong, Fulong Liu, Guoxing Li, Xingchen Yun, Muhammad Yousaf Iqbal, and Fengshou Gu. "Fault identification of the vehicle suspension system based on binocular vision and kinematic decoupling." Mechanical Sciences 15, no. 2 (2024): 445–60. http://dx.doi.org/10.5194/ms-15-445-2024.

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Abstract. Suspension faults have a detrimental impact on the safety and handling stability of a vehicle. Therefore, monitoring the condition of suspension systems is significant to ensuring the safe operation of modern vehicles. This paper proposes an online monitoring scheme that utilizes binocular vision and kinematic decoupling, to fulfill real-time monitoring requirements for suspensions. To implement the proposed method, a system consisting of a binocular camera and an inertial measurement unit (IMU) is established for acquiring vibration signals from the vehicle body. Additionally, the v

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Sanchez Guinea, Alejandro, Simon Heinrich, and Max Mühlhäuser. "Activity-Free User Identification Using Wearables Based on Vision Techniques." Sensors 22, no. 19 (2022): 7368. http://dx.doi.org/10.3390/s22197368.

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In order to achieve the promise of smart spaces where the environment acts to fulfill the needs of users in an unobtrusive and personalized manner, it is necessary to provide means for a seamless and continuous identification of users to know who indeed is interacting with the system and to whom the smart services are to be provided. In this paper, we propose a new approach capable of performing activity-free identification of users based on hand and arm motion patterns obtained from an wrist-worn inertial measurement unit (IMU). Our approach is not constrained to particular types of movements

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Heydarzadeh, Mohsen, Nima Karbasizadeh, Mehdi Tale Masouleh, and Ahmad Kalhor. "Experimental kinematic identification and position control of a 3-DOF decoupled parallel robot." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 5 (2018): 1841–55. http://dx.doi.org/10.1177/0954406218775906.

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This paper aims at using a kinematic identification procedure in order to enhance the control of a 3-DOF fully decoupled parallel robot, the so-called “Tripteron.” From a practical standpoint, manufacture errors lead to some kinematic uncertainties in the robot which cause real kinematic equations of the robot to be different from the theoretical ones. In this paper, using a white box identification procedure, the independence of degrees-of-freedom in the robot is studied. Considering the fact that the kinematic identification of a robotic manipulator requires the position of its end-effector

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Silva, José Luís, Rui Bordalo, José Pissarra, and Paloma de Palacios. "Computer Vision-Based Wood Identification: A Review." Forests 13, no. 12 (2022): 2041. http://dx.doi.org/10.3390/f13122041.

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Wood identification is an important tool in many areas, from biology to cultural heritage. In the fight against illegal logging, it has a more necessary and impactful application. Identifying a wood sample to genus or species level is difficult, expensive and time-consuming, even when using the most recent methods, resulting in a growing need for a readily accessible and field-applicable method for scientific wood identification. Providing fast results and ease of use, computer vision-based technology is an economically accessible option currently applied to meet the demand for automated wood

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Bryła, Jakub, Adam Martowicz, Maciej Petko, Konrad Gac, Konrad Kobus, and Artur Kowalski. "Wear Analysis of 3D-Printed Spur and Herringbone Gears Used in Automated Retail Kiosks Based on Computer Vision and Statistical Methods." Materials 16, no. 16 (2023): 5554. http://dx.doi.org/10.3390/ma16165554.

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This paper focuses on a wear evaluation conducted for prototype spur and herringbone gears made from PET-G filament using additive manufacturing. The main objective of this study is to verify if 3D-printed gears can be considered a reliable choice for long-term exploitation in selected mechanical systems, specifically automated retail kiosks. For this reason, two methods were applied, utilizing: (1) vision-based inspection of the gears’ cross-sectional geometry and (2) the statistical characterization of the selected kinematic parameters and torques generated by drives. The former method invol

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T.A, Sathish Shankar. "Computer Vision based Greenhouse Fruits and Vegetables Identification – A Review." Journal of Innovative Image Processing 6, no. 3 (2024): 290–304. http://dx.doi.org/10.36548/jiip.2024.3.006.

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In recent years, computer vision has emerged as a powerful tool for automating various processes in agriculture, particularly in greenhouse environments. The identification and classification of vegetables and fruits within greenhouses play a crucial role in monitoring crop growth, assessing health status, and optimizing resource utilization. This review study provides a comprehensive overview of recent advancements in computer vision techniques for the identification of vegetables and fruits in greenhouse settings. This study discusses about various methodologies and challenges in this domain

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Dissertations / Theses on the topic "Kinematic identification- Vision based techniques"

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Yang, Xu. "One sample based feature learning and its application to object identification." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950624.

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Werner, Felix. "Vision-based topological mapping and localisation." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/31815/1/Felix_Werner_Thesis.pdf.

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Competent navigation in an environment is a major requirement for an autonomous mobile robot to accomplish its mission. Nowadays, many successful systems for navigating a mobile robot use an internal map which represents the environment in a detailed geometric manner. However, building, maintaining and using such environment maps for navigation is difficult because of perceptual aliasing and measurement noise. Moreover, geometric maps require the processing of huge amounts of data which is computationally expensive. This thesis addresses the problem of vision-based topological mapping and loca

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Anguzza, Umberto. "A method to develop a computer-vision based system for the automaticac dairy cow identification and behaviour detection in free stall barns." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1334.

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In this thesis, a method to develop a computer-vision based system (CVBS) for the automatic dairy cow identification and behaviour detection in free stall barns is proposed. Two different methodologies based on digital image processing were proposed in order to achieve dairy cow identification and behaviour detection, respectively. Suitable algorithms among that used in computer vision science were chosen and adapted to the specific characteristics of the breeding environment under study. The trial was carried out during the years 2011 and 2012 in a dairy cow free-stall barn located in the mu

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Boby, Riby Abraham. "Vision based techniques for kinematic identification of an industrial robot and other devices." Thesis, 2018. http://localhost:8080/iit/handle/2074/7662.

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Kuo, Yao-wen, and 郭耀文. "Vision-based Techniques for Real-time Action Identification of Upper Body Rehabilitation." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/m26nmg.

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碩士<br>國立臺北科技大學<br>資訊工程系研究所<br>101<br>Rehabilitation takes a lot of time to practice rehabilitation actions, and thus causing a shortage of medical and rehabilitation staffs. As a result, home rehabilitation can not only reduce the loadings of family members of rehabilitation pedestrian, but also relieve shortages of medical and rehabilitation staffs, this thesis proposes an action identification of upper body rehabilitation system. For the proposed system, which is the most important point of building upper body skeleton, this thesis presents an algorithm to feasibly and rapidly build upper bo

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Chien, Rong-Chun, and 簡榮均. "Deep Learning Based Computer Vision Techniques for Real-time Identification of Construction Site Personal Equipment Violations." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/x7n995.

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碩士<br>國立臺灣大學<br>土木工程學研究所<br>107<br>Being well-equipped with Personal Protective Equipment (PPE) plays an essential role in construction sites to protect individuals from accidents. However, due to inconvenience and discomfort, it is common to see workers not wearing them on site. Therefore, ensuring the wearing of PPE remains important subject to facilitate construction sites safety. In recent years, because of the increasing performance of graphic cards and the rise of deep learning, Convolutional neural network (CNN) based computer vision techniques is receiving increased attention. Monitori

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Lu, Ming-Kun, and 呂鳴崑. "Multi-Camera Vision-based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Human Computer Interactive Systems." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/vgss3p.

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碩士<br>國立臺北科技大學<br>資訊工程系研究所<br>100<br>Nowadays, multi-touch technology has become a popular issue. Multi-touch has been implemented in several ways including resistive type, capacitive type and so on. However, because of limitations, multi-touch by these implementations cannot support large screens. Therefore, this thesis proposes a multi-camera vision-based finger detection, tracking, and event identification techniques for multi-touch sensing with implementation. The proposed system detects the multi-finger pressing on an acrylic board by capturing the infrared light through four infrared cam

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Books on the topic "Kinematic identification- Vision based techniques"

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MCBR-CDS 2009 (2009 London, England). Medical content-based retrieval for clinical decision support: First MICCAI international workshop, MCBR-CDS 2009, London, UK, September 20, 2009 : revised selected papers. Springer, 2010.

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Feature Dimension Reduction for Content-Based Image Identification. IGI Global, 2018.

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Book chapters on the topic "Kinematic identification- Vision based techniques"

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Fontenla-Carrera, Gabriel, Ángel Manuel Fernández Vilán, and Pablo Izquierdo Belmonte. "Automatic Identification of Kinematic Diagrams with Computer Vision." In Proceedings of the XV Ibero-American Congress of Mechanical Engineering. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-38563-6_62.

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AbstractIn this work, a computer vision algorithm for the detection and recognition of 2D kinematic diagrams, both from paper schemes and digital files, was developed. Furthermore, it runs even with hand-made diagrams, which can be correctly identified. The algorithm is mainly based on the use of the free computer vision library OpenCV, being able to identify each element of the kinematic diagram, its connection with the other elements and store its pixels, which will allow in future research the implementation of motion in the sketches themselves. Allowed elements are revolute, prismatic, fix

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Lele, Jyoti, Naman Palliwal, Sahil Rajurkar, Vibor Tomar, and Anuradha C. Phadke. "Comparison of image based and audio based techniques for bird species identification." In Intelligent Systems and Applications in Computer Vision. CRC Press, 2023. http://dx.doi.org/10.1201/9781003453406-9.

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Harary, Sivan, and Eugene Walach. "Identification of Malignant Breast Tumors Based on Acoustic Attenuation Mapping of Conventional Ultrasound Images." In Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36620-8_23.

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Sajeendran, B. S., and R. Durairaj. "On-Orbit Real-Time Avionics Package Identification Using Vision-Based Machine Learning Techniques." In Lecture Notes in Mechanical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1724-2_41.

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Cruz, Diego A., Cristian C. Cristancho, and Jorge E. Camargo. "Automatic Identification of Traditional Colombian Music Genres Based on Audio Content Analysis and Machine Learning Techniques." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33904-3_61.

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Regmi, Biplav S., Matthew N. Dailey, and Mongkol Ekpanyapong. "Exploring Deep Learning Techniques for Vision-Based Vehicle Re-Identification: A Traffic Intersection Case Study." In Communications in Computer and Information Science. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-7969-1_17.

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Lockner, Yannik, Paul Buske, Maximilian Rudack, et al. "Improving Manufacturing Efficiency for Discontinuous Processes by Methodological Cross-Domain Knowledge Transfer." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_8-1.

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AbstractDiscontinuous processes face common tasks when implementing modeling and optimization techniques for process optimization. While domain data may be unequal, knowledge about approaches for each step toward the solution, e.g., data gathering, model reduction, and model optimization, may be useful across different processes. A joint development of methodologies for machine learning methods, among other things, ultimately supports fast advances in cross-domain production technologies. In this work, an overview of common maturation stages of data-intensive modeling approaches for production

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Lockner, Yannik, Paul Buske, Maximilian Rudack, et al. "Improving Manufacturing Efficiency for Discontinuous Processes by Methodological Cross-Domain Knowledge Transfer." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-44497-5_8.

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AbstractDiscontinuous processes face common tasks when implementing modeling and optimization techniques for process optimization. While domain data may be unequal, knowledge about approaches for each step toward the solution, e.g., data gathering, model reduction, and model optimization, may be useful across different processes. A joint development of methodologies for machine learning methods, among other things, ultimately supports fast advances in cross-domain production technologies. In this work, an overview of common maturation stages of data-intensive modeling approaches for production

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Kavati, Ilaiah, Munaga V. N. K. Prasad, and Chakravarthy Bhagvati. "Search Space Reduction in Biometric Databases." In Computer Vision. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5204-8.ch066.

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Deployment of biometrics for personal recognition in various real time applications lead to large scale databases. Identification of an individual on such large biometric databases using a one-one matching (i.e., exhaustive search) increases the response time of the system. Reducing the search space during identification increases the search speed and reduces the response time of the system. This chapter presents a comprehensive review of the current developments of the search space reduction techniques in biometric databases. Search space reduction techniques for the fingerprint databases are

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Singh, Law Kumar, Pooja, Hitendra Garg, and Munish Khanna. "An Artificial Intelligence-Based Smart System for Early Glaucoma Recognition Using OCT Images." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch073.

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Glaucoma is a progressive and constant eye disease that leads to a deficiency of peripheral vision and, at last, leads to irrevocable loss of vision. Detection and identification of glaucoma are essential for earlier treatment and to reduce vision loss. This motivates us to present a study on intelligent diagnosis system based on machine learning algorithm(s) for glaucoma identification using three-dimensional optical coherence tomography (OCT) data. This experimental work is attempted on 70 glaucomatous and 70 healthy eyes from combination of public (Mendeley) dataset and private dataset. For

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Conference papers on the topic "Kinematic identification- Vision based techniques"

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Manore, Samadhan, M. Sasikumar, and Abhijeet Suryawanshi. "Autonomous Navigation of Robots on Roads using Vision-Based Techniques for Road Identification and Lane Detection." In 2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2024. https://doi.org/10.1109/icarcv63323.2024.10821591.

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Eid, Maged, and Giancarlo Dalle Ave. "Automated Interpretation of Chemical Engineering Diagrams Using Computer Vision." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.129214.

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This paper presents state-of-the-art object detection and object identification algorithms for digitizing and interpreting chemical engineering diagrams, including, Block Flow Diagrams (BFDs), Process Flow Diagrams (PFDs), and Piping and Instrumentation Diagrams (P&IDs), using computer vision techniques. These diagrams are essential for visualizing plant processes and equipment but are often stored as image-based PDFs, making manual digitization/interpretation labor-intensive and error-prone. The proposed algorithm automates tasks such as detecting unit operations and identifying them usin

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Talakoub, Omid, and Farrokh Janabi Sharifi. "A robust vision-based technique for human arm kinematics identification." In Optics East 2006, edited by Yukitoshi Otani and Farrokh Janabi-Sharifi. SPIE, 2006. http://dx.doi.org/10.1117/12.686229.

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Das, Arpita, and Mahua Bhattacharya. "GA Based Neuro Fuzzy Techniques for Breast Cancer Identification." In 2008 International Machine Vision and Image Processing Conference (IMVIP). IEEE, 2008. http://dx.doi.org/10.1109/imvip.2008.19.

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de Figueiredo, Rui Pimentel, and Simon Bøgh. "Vision-Based Corrosion Identification Using Data-Driven Semantic Segmentation Techniques." In 2023 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2023. http://dx.doi.org/10.1109/ist59124.2023.10355698.

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Anil, Abhishek, Hardik Gupta, and Monika Arora. "Computer vision based method for identification of freshness in mushrooms." In 2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT). IEEE, 2019. http://dx.doi.org/10.1109/icict46931.2019.8977698.

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Yang, Shanglin, Yang Lin, Yong Li, Suyi Zhang, Lihui Peng, and Defu Xu. "Machine Vision Based Granular Raw Material Adulteration Identification in Baijiu Brewing." In 2022 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2022. http://dx.doi.org/10.1109/ist55454.2022.9827757.

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Wang, Jin, Mary She, Saeid Nahavandi, and Abbas Kouzani. "A Review of Vision-Based Gait Recognition Methods for Human Identification." In 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2010. http://dx.doi.org/10.1109/dicta.2010.62.

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Gençcelep, Selenay, Volkan Kahya, Kemal Hacıefendioğlu, Sebahat Şimşek, and Tunahan Aslan. "Comparative analysis of vision-based vibration identification techniques using digital camera imaging." In 4th International Civil Engineering & Architecture Conference. Golden Light Publishing, 2025. https://doi.org/10.31462/icearc2025_ce_sme_386.

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Cui, Lulu, Lu Wang, Jinyu Su, Zihan Song, and Xilai Li. "Classification and identification of degraded alpine m eadows based on machine learning techniques." In 2023 4th International Conference on Computer Vision, Image and Deep Learning (CVIDL). IEEE, 2023. http://dx.doi.org/10.1109/cvidl58838.2023.10167398.

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