2nd International Conference On Systems Engineering and Modeling (ICSEM-13)

Abnormal Behavior Detection Based on Global Motion Orientation

Authors
Xuyan Ma, Guomao Liang, Wei Yu, Zhiyi Qu
Corresponding Author
Xuyan Ma
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.89How to use a DOI?
Keywords
abnormal behavior detection, global motion orientation, support vector machine (SVM).
Abstract
A novel approach is introduced in this paper to detect abnormal behavior based on global motion orientation. Compare to the normal behavior (walking, shaking hands etc.), abnormal behavior has different orientation. The method we introduced divides each frame into blocks, makes statistical analysis of the global motion direction histogram of all frame blocks and extracts characteristics. At last, behavior is detected with support vector machine (SVM). Experiment shows that the method proposed in the paper has certain robustness and can achieve real-time monitoring.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-94-91216-42-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/icsem.2013.89How 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  - Xuyan Ma
AU  - Guomao Liang
AU  - Wei Yu
AU  - Zhiyi Qu
PY  - 2013/04
DA  - 2013/04
TI  - Abnormal Behavior Detection Based on Global Motion Orientation
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.89
DO  - https://doi.org/10.2991/icsem.2013.89
ID  - Ma2013/04
ER  -