| Title: | OS26-3 Suspicious Behavior Detection Using Computer Vision |
|---|---|
| Publication: | ICAROB2025 |
| Volume: | 30 |
| Pages: | 729-734 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2025.OS26-3 |
| Author(s): | Dexter Sing Fong Leong, Hao Feng Chan, Shakir Hussain Naushad Mohamed, Wui Chung Alton Chau, Andi Prademon Yunus, Takao Ito, Zheng Cai, Xinjie Deng, Yit Hong Choo |
| Publication Date: | February 13, 2025 |
| Keywords: | Facial Cue, Computer Vision, Deep Learning Models, Suspicious, Surveillance |
| Abstract: | Detecting suspicious activity is a crucial task for public safety. The determination of class suspicious behavior is based on the facial cues of a person. Research has been conducted in this field using computer vision tools. However, accuracy still has room for improvement. Hence, this paper aims to use a novel approach in using other deep learning models to classify behavior as either suspicious or normal based on facial cues. By enhancing the detection process, this paper contributes to improving the reliable and effective surveillance system. |
| PDF File: | https://alife-robotics.co.jp/members2025/icarob/data/html/data/OS/OS26/OS26-3.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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