Share Email Print
cover

Proceedings Paper

Kinect based body posture detection and recognition system
Author(s): Pramod Kumar Pisharady; Martin Saerbeck
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 14 March 2013
PDF: 5 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87687F (14 March 2013); doi: 10.1117/12.2009926
Show Author Affiliations
Pramod Kumar Pisharady, A*STAR Istitute of High Performance Computing (Singapore)
Martin Saerbeck, A*STAR Istitute of High Performance Computing (Singapore)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

© SPIE. Terms of Use
Back to Top