In this paper constrained contour models are applied for hand posture-recognition in single color images. In particular, the proposed algorithm utilizes a class of physics-based modelling methods called Deformable Templates [1],[2],[3]. After color-based image segmentation a contour hypothesis is detected and some features are extracted, suitable for comparison with the template's geometric properties. Several metrics for matching contour templates against image data are discussed. The described methods are evaluated experimentally and referred to a known hand posture recognition algorithm.
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