Abnormal Behavior Detection Based on Global Motion Orientation
Xuyan Ma, Guomao Liang, Wei Yu, Zhiyi Qu
Available Online April 2013.
- https://doi.org/10.2991/icsem.2013.89How to use a DOI?
- abnormal behavior detection, global motion orientation, support vector machine (SVM).
- 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.
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 SP - 461 EP - 464 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 -