AVS-Net: Automatic Visual Surveillance Using Relation Network

Visual surveillance through closed circuit television (CCTV) can help to prevent crime. In this paper, we propose an automatic visual surveillance network (AVS-Net), which simultaneously performs image processing and object detection to determine the dangers of situations captured by CCTV. In addition, we add a relation module to infer the relationships of the objects in the images. Experimental results show that the relation module greatly improves classification accuracy, even if there is not enough information.

Authors

• Sein Jang
• Young-Ho Park
• Aziz Nasridinov Chungbuk National University

Keywords

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