基于时空纹理特征的3D人体行为分析系统

urrently 3D human behavior videos containing depth information have been widely applied to areas of body sensing interaction and behavior analysis. In order to better analyze human behavior in real-life scenarios, a human behavior video recognition method and system is proposed based on temporal texture features. First of all, Kinect and other somatosensory equipment are employed to capture human behavior videos, which are then preprocessed. Afterwards, the three-dimensional temporal texture features are extracted to generate a human behavior feature information model; then classification and recognition is accomplished and analog personality control is realized on the behavior analysis system. Compared to previous recognition methods, the proposed method has simplified the complexity of human behavior recognition in the videos, reduced the data size of behavioral features, and achieved good system analysis results.