Limb-based feature description of human motion



Publication Details

Adistambha, K., Davis, S. J., Ritz, C. H. & Stirling, D. A. (2011). Limb-based feature description of human motion. ICSPCS'2011: 5th International Conference on Signal Processing and Telecommunication Systems (pp. 1-6). New York: IEEE.


This paper proposes a novel limb-based technique for semantic description of motion capture data. The goal is to create a motion segmentation and classification technique that is easily extensible by recognizing the actions of a limb instead of the whole body. This provides a highly detailed metadata that can be extended as needed to include additional motion classes by either adding a new limb submotion or by defining a new full-body motion class that combines existing known limb movements. The results of the initial implementation for annotating the leg movements (forward and backward) of walking and running show that such a system is feasible, with annotation accuracy of more than 98%.

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