Video based human activities recognition using deep learning
Human activities recognition from motion capture data is a challenging problem in the computer vision due to the fact that, in various human activities, different body components have distinctive characteristics in terms of the moving pattern. In this paper, a learning method of detecting an activi...
| Main Authors: | , |
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| Format: | Proceeding Paper |
| Language: | English English English |
| Published: |
AIP Publishing
2020
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/82391/ http://irep.iium.edu.my/82391/18/82391_Video%20Based%20Human%20Activities%20Recognition%20using%20Deep_new.pdf http://irep.iium.edu.my/82391/7/Notification%20of%20Acceptance%20ICEDSA%202020%20%20%2327%20%20%20Video%20Based%20Human%20Activities%20Recognition%20Using%20Deep%20learning.pdf http://irep.iium.edu.my/82391/13/Certificate%20%20ICEDSA%202020%20%20%2327%20%20%20Video%20Based%20Human%20Activities%20Recognition%20Using%20Deep%20learning.pdf |
| _version_ | 1848789291204870144 |
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| author | Roubleh, A. A. Khalifa, Othman Omran |
| author_facet | Roubleh, A. A. Khalifa, Othman Omran |
| author_sort | Roubleh, A. A. |
| building | IIUM Repository |
| collection | Online Access |
| description | Human activities recognition from motion capture data is a challenging problem in the computer vision due to the fact that, in various human activities, different body components have distinctive characteristics in terms of the moving pattern. In this paper, a learning method of detecting an activities from different angles based on various sources of information is proposed. with high accuracy. The bottomup approach is used in OpenPose which is the tool used in this paper’s experiments The proposed method achieve promising results on the MHAD datasets at 98% accuracy. |
| first_indexed | 2025-11-14T17:54:23Z |
| format | Proceeding Paper |
| id | iium-82391 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-14T17:54:23Z |
| publishDate | 2020 |
| publisher | AIP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-823912020-12-30T08:15:53Z http://irep.iium.edu.my/82391/ Video based human activities recognition using deep learning Roubleh, A. A. Khalifa, Othman Omran T Technology (General) Human activities recognition from motion capture data is a challenging problem in the computer vision due to the fact that, in various human activities, different body components have distinctive characteristics in terms of the moving pattern. In this paper, a learning method of detecting an activities from different angles based on various sources of information is proposed. with high accuracy. The bottomup approach is used in OpenPose which is the tool used in this paper’s experiments The proposed method achieve promising results on the MHAD datasets at 98% accuracy. AIP Publishing 2020-03-28 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/82391/18/82391_Video%20Based%20Human%20Activities%20Recognition%20using%20Deep_new.pdf application/pdf en http://irep.iium.edu.my/82391/7/Notification%20of%20Acceptance%20ICEDSA%202020%20%20%2327%20%20%20Video%20Based%20Human%20Activities%20Recognition%20Using%20Deep%20learning.pdf application/pdf en http://irep.iium.edu.my/82391/13/Certificate%20%20ICEDSA%202020%20%20%2327%20%20%20Video%20Based%20Human%20Activities%20Recognition%20Using%20Deep%20learning.pdf Roubleh, A. A. and Khalifa, Othman Omran (2020) Video based human activities recognition using deep learning. In: 7th International Conference on Electronic Devices, Systems and Applications (ICEDSA2020), 28th - 29th March 2020, Shah Alam, Selangor. https://aip.scitation.org/doi/10.1063/5.0032379 10.1063/5.0032379 |
| spellingShingle | T Technology (General) Roubleh, A. A. Khalifa, Othman Omran Video based human activities recognition using deep learning |
| title | Video based human activities recognition using deep learning |
| title_full | Video based human activities recognition using deep learning |
| title_fullStr | Video based human activities recognition using deep learning |
| title_full_unstemmed | Video based human activities recognition using deep learning |
| title_short | Video based human activities recognition using deep learning |
| title_sort | video based human activities recognition using deep learning |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/82391/ http://irep.iium.edu.my/82391/ http://irep.iium.edu.my/82391/ http://irep.iium.edu.my/82391/18/82391_Video%20Based%20Human%20Activities%20Recognition%20using%20Deep_new.pdf http://irep.iium.edu.my/82391/7/Notification%20of%20Acceptance%20ICEDSA%202020%20%20%2327%20%20%20Video%20Based%20Human%20Activities%20Recognition%20Using%20Deep%20learning.pdf http://irep.iium.edu.my/82391/13/Certificate%20%20ICEDSA%202020%20%20%2327%20%20%20Video%20Based%20Human%20Activities%20Recognition%20Using%20Deep%20learning.pdf |