Kinect based body posture detection and recognition system
Pramod Kumar Pisharady, Martin Saerbeck · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
A multi-class human posture detection and recognition algorithm using Kinect based geometric features is presented. The three dimensional skeletal data from the Kinect is converted to a set of angular features. The postures are classified using a support vector machines classifier with polynomial kernel. Detection of posture is done by thresholding the posture probability. The algorithm provided a recognition accuracy of 95.78% when tested using a 10 class dataset containing 6000 posture samples. The precision and recall rates of the detection system are 100% and 98.54% respectively.