Suspicious Behavior Detection Using Computer Vision
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.
Authors
- Andi Prademon Yunus (ORCID: https://orcid.org/0000-0002-1185-5763)
- Shady Mohamed (ORCID: https://orcid.org/0000-0002-8851-1635)
- Xinjie Deng
- Hao Feng Chan
- Takao Ito (ORCID: https://orcid.org/0000-0001-6224-5204)
- Yit Hong Choo (ORCID: https://orcid.org/0000-0002-2490-1925)
- Zheng Cai (ORCID: https://orcid.org/0009-0002-1775-5752)
- Dexter Sing Fong Leong
- Wui Chung Alton Chau
Institutions
- Hiroshima University (JP)
- Deakin University (AU)
- Telkom University (ID)
Publication Details
- Journal
- Proceedings of International Conference on Artificial Life and Robotics
- Published
- 2025-02-13
- DOI
- https://doi.org/10.5954/icarob.2025.os26-3
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00