Human detection in video is an important task for security surveillance systems. It could help reducing time and effort when tracking a human in a long video such as finding a thief in video of surveillance camera. This study proposes an approach to build an application of recognizing and detecting human in videos. The purpose of this application is to trace, investigate, or review the events that have taken place from the security camera when the need arises. In this work, we have compared there methods (pre-trained Yolov7, self-defined sequential model, and VGG16 Transfer Learning) for detecting human in the video. Experiments are built using data set which is extracted from security camera with several angles and different resolutions. The approach has achieved results with the highest accuracy of 97% for human recognition, thus, it would be a good solution for practice
Tạp chí: International scientific conference proceedings “Enhancing cooperation to promote sustainable tourism in response to climate change, the fourth industrial revolution and artificial intelligence" 2024, Trường Đại học Nam Cần Thơ
Tạp chí: 8th International ICONTECH CONGRESS on Innovative Surveys in Positive Sciences, March 16-18, 2024, Azerbaijan Cooperation University, Baku, Azerbaijan
Tạp chí khoa học Trường Đại học Cần Thơ
Lầu 4, Nhà Điều Hành, Khu II, đường 3/2, P. Xuân Khánh, Q. Ninh Kiều, TP. Cần Thơ
Điện thoại: (0292) 3 872 157; Email: tapchidhct@ctu.edu.vn
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