Abstract: With Microsoft’s announcement of a permanent discontinuation of Kinect products in October 2017, there is an urgent need for a Kinect replacement in the field of somatosensory interaction. This article uses a normal monocular camera to read the video stream in real time. The Faster-RCNN network is used to detect the position of the human body and frame the human body. The non-maximum suppression algorithm is improved, and a linear weighting function is introduced to reduce the detection frame score of the IOU greater than the threshold instead of becoming zero. Secondly, according to the obtained detection frame, the CPM network is detected by the key points of the human body, and the coordinate position of the whole body skeleton point is outputted, and Center Loss is introduced to increase the cohesiveness and inter-class difference of the intra-class features of the key points. Finally, according to the template matching method, a control instruction of the somatosensory interaction is generated according to the recognition result. The method of this paper reduces the dependence on professional equipment, simplifies the complexity of somatosensory interaction, and has important value for promoting the popularity of somatosensory and expanding the scope of human-computer interaction.

Key words: somatosensory interaction, Faster-RCNN, CPM, non-maximum suppression, center loss