Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society

Human Abnormal Behavior Detection Based on Region Optical Flow Energy

Authors
Jian Liu, Lin Qiu, Enyang Gao
Corresponding Author
Jian Liu
Available Online April 2016.
DOI
https://doi.org/10.2991/emim-16.2016.216How to use a DOI?
Keywords
Anomaly detection; Foreground extraction; Vibe algorithm; Optical flow calculation; Energy histogram
Abstract
In the light of the hysteresis of video surveillance call video in public places, as well as the current video surveillance function of a single, in order to improve the real-time performance of monitoring, a detection method of human abnormal behavior based on optical flow method is proposed. The foreground regions of the video sequence is obtained by Vibe algorithm and update the background model adaptively; Regional markers for the future by the nearest neighbor method, accurately extract moving regions; Optical flow of moving region is calculated by Lucas-Kanada method; Weighted energy histogram is used to describe the abnormal changes of human behavior. The video sequences of different scenarios are simulated; the experimental results verify the effectiveness of the proposed method.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
6th International Conference on Electronic, Mechanical, Information and Management Society
Part of series
Advances in Computer Science Research
Publication Date
April 2016
ISBN
978-94-6252-176-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/emim-16.2016.216How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jian Liu
AU  - Lin Qiu
AU  - Enyang Gao
PY  - 2016/04
DA  - 2016/04
TI  - Human Abnormal Behavior Detection Based on Region Optical Flow Energy
BT  - 6th International Conference on Electronic, Mechanical, Information and Management Society
PB  - Atlantis Press
SP  - 1050
EP  - 1057
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-16.2016.216
DO  - https://doi.org/10.2991/emim-16.2016.216
ID  - Liu2016/04
ER  -