14 March 2013 Kinect based body posture detection and recognition system
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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.
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Pramod Kumar Pisharady, Pramod Kumar Pisharady, Martin Saerbeck, 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); doi: 10.1117/12.2009926; https://doi.org/10.1117/12.2009926
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