Hybrid Attention and Motion Constraint for Anomaly Detection in Crowded Scenes-Reference-Cited by-同舟云学术

Hybrid Attention and Motion Constraint for Anomaly Detection in Crowded Scenes

Published:2023-05 Issue:5 Volume:33 Page:2259-2274
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Zhang Xinfeng¹^ORCID,Fang Jinpeng¹^ORCID,Yang Baoqing¹,Chen Shuhan¹^ORCID,Li Bin¹

Affiliation:

1. Jiangsu Province Engineering Research Center of Knowledge Management and Intelligent Service, College of Information Engineering (College of Artificial Intelligence), Yangzhou University, Jiangsu, Yangzhou, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Higher Education Institutions of China

Yangzhou University “Qinglan Project”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10116045/09945995.pdf?arnumber=9945995

Reference44 articles.

1. A thermodynamics-inspired feature for anomaly detection on crowd motions in surveillance videos

2. Anomaly detection in crowded scenes

3. Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection

4. Abnormal Event Detection at 150 FPS in MATLAB

5. Spatio-Temporal AutoEncoder for Video Anomaly Detection

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