AVS-Net: Automatic Visual Surveillance Using Relation Network

Authors

  • Sein Jang Chungbuk National University
  • Young-Ho Park Sookmyung Women's University
  • Aziz Nasridinov Chungbuk National University

DOI:

https://doi.org/10.1609/aaai.v33i01.33019947

Abstract

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.

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Published

2019-07-17

How to Cite

Jang, S., Park, Y.-H., & Nasridinov, A. (2019). AVS-Net: Automatic Visual Surveillance Using Relation Network. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9947-9948. https://doi.org/10.1609/aaai.v33i01.33019947

Issue

Section

Student Abstract Track