Abnormal Behavior Detection Based on Dynamic Pedestrian Centroid Model: Case Study on U-Turn and Fall-Down
Author:
Affiliation:
1. CIMS Research Center, Tongji University, Shanghai, China
2. College of Electronic and Information Engineering, Tongji University, Shanghai, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10202228/10101700.pdf?arnumber=10101700
Reference34 articles.
1. An Analysis Method of Crowd Abnormal Behavior for Video Service Robot
2. Variational Abnormal Behavior Detection With Motion Consistency
3. Ergonomic postural assessment using a new open-source human pose estimation technology (OpenPose)
4. A weakly supervised framework for abnormal behavior detection and localization in crowded scenes
5. Efficient Anomaly Detection in Crowd Videos Using Pre-Trained 2D Convolutional Neural Networks
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