Two dimensional discrete statistical shape models construction

In this paper, we present a discrete approach to 2D statistical shape models construction. An object is modeled in terms of landmark points on its contour. An optimized process of intrinsic discrete properties computes then curvilinear position, curvature and normal vector for each point. The approach uses after a dynamic programming process to match points of different shapes. By identifying matched points on a set of training examples, a statistical approach with principal component analysis, computes the mean object shape, the major modes of shape variation and extracts a compact and generic model.

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