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Summary of proposed method Home service robots must possess the ability to communicate  with humans, for which human detection and recognition  methods are particularly important.  This paper proposes methods for human detection and face  recognition that are based on image processing, and are  suitable for home service robots.  For the human detection method, we combine the method  proposed by Xia et al. based on the use of head shape with  the results of region segmentation based on depth  information, and use the positional relations of the  detected points.  We obtained a detection rate of 98.1% when the method was  evaluated for various postures and facing directions.  We demonstrate the robustness of the proposed method  against postural changes such as stretching the arms,  resting the chin on one’s hands, and drinking beverages.  For the human recognition method, we combine the elastic  bunch graph matching method proposed by Wiskott et al. with  Face Tracking SDK to extract facial feature points, and use  the 3D information in the deformation computation; we  obtained a recognition rate of 93.6% during evaluation.

Human Detection and Face Recognition Using 3D Structure of Head and Face Surfaces Detected by RGB-D Sensor