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2019 AAAI AAAI 2019

AVS-Net: Automatic Visual Surveillance Using Relation Network

Abstract

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.

🚀 Conference Pioneer — AAAI 2019
🌉 Interdisciplinary Bridge — Computer Vision and Deep Learning
🧭 Keyword Pioneer — visual surveillance
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Sein Jang , Young-Ho Park , Aziz Nasridinov

Topics

Deep Learning > Architectures > Neural Networks Computer Vision > Analysis > Object Detection Computer Vision > Analysis > Scene Understanding

Keywords

scene understanding object detection image processing visual surveillance relation network neural network
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