Human arm-motion classification using qualitative normalised templates

Authors:
Chee Seng Chan;Honghai Liu;David J. Brown
Affiliations:
Institute of Industrial Research, The University of Portsmouth, Portsmouth, England (UK);Institute of Industrial Research, The University of Portsmouth, Portsmouth, England (UK);Institute of Industrial Research, The University of Portsmouth, Portsmouth, England (UK)
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Year:
2006

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Abstract

This paper proposes an approach to classify human arm motion using qualitative normalized templates. The proposed method consists of construction of human arm model, qualitative representation of prior knowledge of human arm motion and a search algorithm. First, convention robotic model is employed to build up a generic vision model for a human arm; Secondly, qualitative robotic model in [1] is used to construct qualitative normalised templates; Finally a search algorithm is provided to match the vision model with the templates in image frames. Experimental evaluation demonstrates that the proposed method is effective for the classification of human-arm motion. Future work will focus on extending the proposed method to the classification of a full human-body motion.