We introduce a system that exploits 3-D imaging technology as an enabler for the robust recognition of the human form. We combine this with pose and feature recognition capabilities from which we can recognise high-level human behaviours. We propose a hierarchical methodology for the recognition of complex human behaviours, based on the identification of a set of atomic behaviours, individual and sequential poses (e.g. standing, sitting, walking, drinking and eating) that provides a framework from which we adopt time-based machine learning techniques to recognise complex behaviour patterns.
Bo Yao, Jason J. Lepley, Robert Peall, Michael Butler, and Hani Hagras, "Recognition of complex human behaviours using 3D imaging for intelligent surveillance applications," Proc. SPIE 9992, Emerging Imaging and Sensing Technologies, 99920H (Presented at SPIE Security + Defence: September 29, 2016; Published: 25 October 2016); https://doi.org/10.1117/12.2241088.
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