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We propose a method for real-time human pose and gesture recognition for autonomous robots using a structured light 3D-scanner. Poses are recognized using skeleton representations by performing classification using the Nearest Neighbour algorithm. The whole-body pose recognition approach uses the joint coordinate data from the processed depth images. The quality of the classification is determined by 10-fold cross validation in which the recognition rate is 99.9028%.
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