A review of machine vision pose measurement
This review paper provides a comprehensive overview of machine vision pose measurement algorithms. The paper focuses on the state-of-the-art algorithms and their applications. The paper is structured as follows: the introduction in provides a brief overview of the field of machine vision pose measur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/116397/ http://psasir.upm.edu.my/id/eprint/116397/1/116397.pdf |
| _version_ | 1848866994819956736 |
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| author | Xiaoxiao, Wang Beng, Ng Seng O. K. Rahmat, Rahmita Wirza Sulaima, Puteri Suhaiza |
| author_facet | Xiaoxiao, Wang Beng, Ng Seng O. K. Rahmat, Rahmita Wirza Sulaima, Puteri Suhaiza |
| author_sort | Xiaoxiao, Wang |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This review paper provides a comprehensive overview of machine vision pose measurement algorithms. The paper focuses on the state-of-the-art algorithms and their applications. The paper is structured as follows: the introduction in provides a brief overview of the field of machine vision pose measurement. Describes the commonly used algorithms for machine vision pose measurement. Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. Summarizes the paper and provides future research directions. The paper highlights the need for more robust and accurate algorithms that can handle varying lighting conditions and occlusion. It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. Overall, this review paper provides a comprehensive overview of machine vision pose measurement algorithms, their applications, and the factors that affect their accuracy and reliability. It provides a valuable resource for researchers and practitioners working in the field of computer vision. |
| first_indexed | 2025-11-15T14:29:27Z |
| format | Article |
| id | upm-116397 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:29:27Z |
| publishDate | 2024 |
| publisher | Institute of Advanced Engineering and Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1163972025-03-28T04:03:36Z http://psasir.upm.edu.my/id/eprint/116397/ A review of machine vision pose measurement Xiaoxiao, Wang Beng, Ng Seng O. K. Rahmat, Rahmita Wirza Sulaima, Puteri Suhaiza This review paper provides a comprehensive overview of machine vision pose measurement algorithms. The paper focuses on the state-of-the-art algorithms and their applications. The paper is structured as follows: the introduction in provides a brief overview of the field of machine vision pose measurement. Describes the commonly used algorithms for machine vision pose measurement. Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. Summarizes the paper and provides future research directions. The paper highlights the need for more robust and accurate algorithms that can handle varying lighting conditions and occlusion. It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. Overall, this review paper provides a comprehensive overview of machine vision pose measurement algorithms, their applications, and the factors that affect their accuracy and reliability. It provides a valuable resource for researchers and practitioners working in the field of computer vision. Institute of Advanced Engineering and Science 2024-10 Article PeerReviewed text en cc_by_sa_4 http://psasir.upm.edu.my/id/eprint/116397/1/116397.pdf Xiaoxiao, Wang and Beng, Ng Seng and O. K. Rahmat, Rahmita Wirza and Sulaima, Puteri Suhaiza (2024) A review of machine vision pose measurement. Indonesian Journal of Electrical Engineering and Computer Science, 36 (1). pp. 450-460. ISSN 2502-4752; eISSN: 2502-4760 https://ijeecs.iaescore.com/index.php/IJEECS/article/view/36538 10.11591/ijeecs.v36.i1.pp450-460 |
| spellingShingle | Xiaoxiao, Wang Beng, Ng Seng O. K. Rahmat, Rahmita Wirza Sulaima, Puteri Suhaiza A review of machine vision pose measurement |
| title | A review of machine vision pose measurement |
| title_full | A review of machine vision pose measurement |
| title_fullStr | A review of machine vision pose measurement |
| title_full_unstemmed | A review of machine vision pose measurement |
| title_short | A review of machine vision pose measurement |
| title_sort | review of machine vision pose measurement |
| url | http://psasir.upm.edu.my/id/eprint/116397/ http://psasir.upm.edu.my/id/eprint/116397/ http://psasir.upm.edu.my/id/eprint/116397/ http://psasir.upm.edu.my/id/eprint/116397/1/116397.pdf |