The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks
Video surveillance is one of the best tools available today for detecting and preventing workplace fraud and other unwanted activity. This study aims to find the presence of human activity (no activity or activity) in the CCTV video footage. This study develops a novel algorithm called NovelHAD base...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Cogent Social Sciences |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23311886.2025.2474863 |
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| author | Y. V. K. Durga Bhavani V. B. Pagi |
| author_facet | Y. V. K. Durga Bhavani V. B. Pagi |
| author_sort | Y. V. K. Durga Bhavani |
| collection | DOAJ |
| description | Video surveillance is one of the best tools available today for detecting and preventing workplace fraud and other unwanted activity. This study aims to find the presence of human activity (no activity or activity) in the CCTV video footage. This study develops a novel algorithm called NovelHAD based on the human kinematic prototype anatomy and the MediaPipe Pose (MPP) landmark detector feature extraction technique. The movements toward a person’s hands and legs indicate human activity. The distances between the human landmarks or feature vectors (LEFT_HIP, LEFT_ELBOW), (RIGHT_HIP, RIGHT_ELBOW), and (LEFT_ANKLE, RIGHT_ANKLE) were measured in Euclidean space to capture the motions. The UCF-101 Crime public dataset is used to investigate the presence of human activity. The experiment’s findings indicate a 95% accuracy. |
| format | Article |
| id | doaj-art-5ee05209180a4996bc9099d16a2aa44f |
| institution | DOAJ |
| issn | 2331-1886 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Social Sciences |
| spelling | doaj-art-5ee05209180a4996bc9099d16a2aa44f2025-08-20T03:12:11ZengTaylor & Francis GroupCogent Social Sciences2331-18862025-12-0111110.1080/23311886.2025.2474863The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarksY. V. K. Durga Bhavani0V. B. Pagi1Department of Computer Science and Engineering, Basaveshwar Engineering College Research Center, Bagalkote, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, IndiaDepartment of Computer Science and Engineering, Basaveshwar Engineering College Research Center, Bagalkote, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, IndiaVideo surveillance is one of the best tools available today for detecting and preventing workplace fraud and other unwanted activity. This study aims to find the presence of human activity (no activity or activity) in the CCTV video footage. This study develops a novel algorithm called NovelHAD based on the human kinematic prototype anatomy and the MediaPipe Pose (MPP) landmark detector feature extraction technique. The movements toward a person’s hands and legs indicate human activity. The distances between the human landmarks or feature vectors (LEFT_HIP, LEFT_ELBOW), (RIGHT_HIP, RIGHT_ELBOW), and (LEFT_ANKLE, RIGHT_ANKLE) were measured in Euclidean space to capture the motions. The UCF-101 Crime public dataset is used to investigate the presence of human activity. The experiment’s findings indicate a 95% accuracy.https://www.tandfonline.com/doi/10.1080/23311886.2025.2474863KinematiclandmarksMediaPipeposeArtificial IntelligenceComputer Engineering |
| spellingShingle | Y. V. K. Durga Bhavani V. B. Pagi The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks Cogent Social Sciences Kinematic landmarks MediaPipe pose Artificial Intelligence Computer Engineering |
| title | The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks |
| title_full | The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks |
| title_fullStr | The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks |
| title_full_unstemmed | The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks |
| title_short | The NovelHAD algorithm to detect presence of human activity in videos based on MediaPipe pose and human landmarks |
| title_sort | novelhad algorithm to detect presence of human activity in videos based on mediapipe pose and human landmarks |
| topic | Kinematic landmarks MediaPipe pose Artificial Intelligence Computer Engineering |
| url | https://www.tandfonline.com/doi/10.1080/23311886.2025.2474863 |
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