Abstract
Segmentation is a first and important step in video-based motion capture applications. A lack of constraints can make this process daunting and difficult to achieve. We propose a technique that makes use of an improved JSEG procedure in the context of markerless motion capture for performance evaluation of human beings in unconstrained environments. In the proposed algorithm a non-parametric clustering of image data is performed in order to produce homogenous colour-texture regions. The clusters are modified using soft –classifications and allow the J-Value segmentation to deal with smooth colour and lighting transitions. The regions are adapted using an original merging and video stack tracking algorithm.
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Côté, M., Payeur, P., Comeau, G. (2007). Video Segmentation for Markerless Motion Capture in Unconstrained Environments. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_78
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DOI: https://doi.org/10.1007/978-3-540-76856-2_78
Publisher Name: Springer, Berlin, Heidelberg
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