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.

AAAI-19 Proceedings Cover

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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

Vol. 33 No. 01: AAAI-19, IAAI-19, EAAI-20

Section

Student Abstract Track