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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Chan, C. S., Liu, H., & Brown, D. J. (2006). Human arm-motion classification using qualitative normalised templates. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4251 LNAI-I, pp. 639–646). Springer Verlag. https://doi.org/10.1007/11892960_77
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