Presenter(s)

    Manish Pavan Beesetti

    Comments

    This poster reflects research conducted as part of a course project designed to give students experience in the research process. Course: CPS 592

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    Description

    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.

    Publication Date

    4-22-2021

    Project Designation

    Course Project

    Primary Advisor

    Van Tam Nguyen

    Primary Advisor's Department

    Computer Science

    Keywords

    Stander Symposium project, College of Arts and Sciences

    United Nations Sustainable Development Goals

    Peace, Justice, and Strong Institutions

    Human Behavioral Analysis: Intruder Detection in Videos

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