1. Abnormal Behavior Detection Based on Global Motion Orientation
- Author
-
Zhi Yi Qu, Xu Yan Ma, Wei Yu, and Guo Mao Liang
- Subjects
Engineering ,business.industry ,Orientation (computer vision) ,Frame (networking) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,General Engineering ,Motion (physics) ,Support vector machine ,Robustness (computer science) ,Histogram ,Computer vision ,Artificial intelligence ,Shaking hands ,Abnormality ,business - 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.
- Published
- 2013