Manish Pavan Beesetti
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This research aims to develop an intruder detection system based on human behavior via front door surveillance. This is similar to the classic action recognition and scene recognition problems which are currently hot topics in the field of computer vision. To this end, we have collected YouTube videos and then annotate them as anomaly or normal labels. We then train a C3D model by considering a sequence of frames as an input. The experimental results demonstrate the effectiveness of our system.
Van Tam Nguyen
Primary Advisor's Department
Stander Symposium Posters, College of Arts and Sciences
United Nations Sustainable Development Goals
Peace, Justice, and Strong Institutions
"Human Behavioral Analysis: Intruder Detection in Videos" (2021). Stander Symposium Projects. 2151.