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Towards a Professional Gesture Recognition with RGB-D from Smartphone
Abstract. The goal of this work is to build the basis for a smartphone application that provides functionalities for recording human motion data, train machine learning algorithms and recognize professional gestures. First, we take advantage of the new mobile phone cameras, either infrared or stereoscopic, to record RGB-D data. Then, a bottom-up pose estimation algorithm based on Deep Learning extracts the 2D human skeleton and exports the 3rd dimension using the depth. Finally, we use adoi:10.5281/zenodo.3732961 fatcat:ogyignilu5d2zh3mel5wxazdga