Kinect based body posture detection and recognition system

Pramod Kumar Pisharady; Martin Saerbeck

doi:10.1117/12.2009926

14 March 2013 Kinect based body posture detection and recognition system

Pramod Kumar Pisharady, Martin Saerbeck

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87687F (2013) https://doi.org/10.1117/12.2009926
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

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.

Citation Download Citation

Pramod Kumar Pisharady and Martin Saerbeck "Kinect based body posture detection and recognition system", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87687F (14 March 2013); https://doi.org/10.1117/12.2009926

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