Human Gait Recognition Based on Multi-Feature Fusion and Kinect Sensor

Gait recognition has gained increasing attention from biometric scholars because of its applications in video surveillance. A novel approach to recognize human gait is presented based on multi-feature fusion and nearest neighbor classifier. The developed method firstly extracts 3 kinds of features from gait skeletal data by exploiting Kinect followed by calculating distances between any 2 gait sequences corresponding to these features. In what follows, weighted summation can be applied to acquire one fusion that is used in nearest neighbor classifier to recognize any gait sequence. The effectiveness of this gait recognition algorithm is verified on UPCV gait database and the experimental results show that the method has encouraging recognition rate.