Detection of Crowd concentrations with YOLO V3
Crowd detection using street cameras has attracted a lot of research in recent years. In this paper, we propose a simple, fast, and effective method using YOLOv3 model for crowd detection. Using image frames extracted from surveillance video, pedestrian objects are detected, counted and a warning s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Can Tho University Publisher
2023-10-01
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| Series: | CTU Journal of Innovation and Sustainable Development |
| Subjects: | |
| Online Access: | https://ctujs.ctu.edu.vn/index.php/ctujs/article/view/685 |
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| _version_ | 1850185216933494784 |
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| author | Ba Duy Nguyen Thanh Nhan Dinh Thanh Bach Nguyen Quoc Dinh Truong |
| author_facet | Ba Duy Nguyen Thanh Nhan Dinh Thanh Bach Nguyen Quoc Dinh Truong |
| author_sort | Ba Duy Nguyen |
| collection | DOAJ |
| description |
Crowd detection using street cameras has attracted a lot of research in recent years. In this paper, we propose a simple, fast, and effective method using YOLOv3 model for crowd detection. Using image frames extracted from surveillance video, pedestrian objects are detected, counted and a warning signal is sent out when a crowd occurs. The obtained results on test data extracted from 2 data sets STCrowd, SmartCity, and our self-collected dataset confirm the feasibility of the proposed method.
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| format | Article |
| id | doaj-art-a8425a02d9ad43fbbab36c72b8512af9 |
| institution | OA Journals |
| issn | 2588-1418 2815-6412 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | Can Tho University Publisher |
| record_format | Article |
| series | CTU Journal of Innovation and Sustainable Development |
| spelling | doaj-art-a8425a02d9ad43fbbab36c72b8512af92025-08-20T02:16:49ZengCan Tho University PublisherCTU Journal of Innovation and Sustainable Development2588-14182815-64122023-10-0115Special issue: ISDS10.22144/ctujoisd.2023.035Detection of Crowd concentrations with YOLO V3Ba Duy Nguyen0Thanh Nhan Dinh1Thanh Bach Nguyen2Quoc Dinh TruongCan Tho University of TechnologyCan Tho University of TechnologyTra Vinh Provincial Police Department Crowd detection using street cameras has attracted a lot of research in recent years. In this paper, we propose a simple, fast, and effective method using YOLOv3 model for crowd detection. Using image frames extracted from surveillance video, pedestrian objects are detected, counted and a warning signal is sent out when a crowd occurs. The obtained results on test data extracted from 2 data sets STCrowd, SmartCity, and our self-collected dataset confirm the feasibility of the proposed method. https://ctujs.ctu.edu.vn/index.php/ctujs/article/view/685Object detectioncrowded scenceYOLOv3 model |
| spellingShingle | Ba Duy Nguyen Thanh Nhan Dinh Thanh Bach Nguyen Quoc Dinh Truong Detection of Crowd concentrations with YOLO V3 CTU Journal of Innovation and Sustainable Development Object detection crowded scence YOLOv3 model |
| title | Detection of Crowd concentrations with YOLO V3 |
| title_full | Detection of Crowd concentrations with YOLO V3 |
| title_fullStr | Detection of Crowd concentrations with YOLO V3 |
| title_full_unstemmed | Detection of Crowd concentrations with YOLO V3 |
| title_short | Detection of Crowd concentrations with YOLO V3 |
| title_sort | detection of crowd concentrations with yolo v3 |
| topic | Object detection crowded scence YOLOv3 model |
| url | https://ctujs.ctu.edu.vn/index.php/ctujs/article/view/685 |
| work_keys_str_mv | AT baduynguyen detectionofcrowdconcentrationswithyolov3 AT thanhnhandinh detectionofcrowdconcentrationswithyolov3 AT thanhbachnguyen detectionofcrowdconcentrationswithyolov3 AT quocdinhtruong detectionofcrowdconcentrationswithyolov3 |