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Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications. We propose a new approach to extract human joints (Vertex positions)using a model-based method. The gait pattern is incorporated to aid the extraction process, where model templates are established through analysis of gait motion. People walk normal to the viewing plane, as major gait information is available in a sagittal view. Gait periodicity and other parameters are estimated by finding the heel strikes. The ankle, knee and hip joints are successfully extracted with high accuracy for indoor and outdoor data. In this way, we have established a baseline analysis which can be deployed in recognition, marker-less analysis and other areas.

Item Type	Conference
Divisions
ePrint ID	106
Date Deposited	2014-10-30
Further Information	Google Scholar
URI	https://univ-soukahras.dz/en/publication/article/106

@inproceedings{uniusa106,
    title={Markerless Feature Extraction for Gait Analysis},
    author={Imed BOUCHRIKA and M. S. Nixon},
    year={2006},
    booktitle={IEEE SMC Chapter Conference on Advanced in Cybernetic Systems}
}