IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Organization and Curve Partitioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape matching using curvature processes
Computer Vision, Graphics, and Image Processing
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Locating Perceptually Salient Points on Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
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2D curve representations usually take algebraic forms in ways not related to visual perception. This poses great difficulties in connecting curve representation with object recognition where information computed from raw images must be manipulated in a perceptually meaningful way and compared to the representation. In this paper we show that 2D curves can be represented compactly by imposing shaping constraints in curvature space, which can be readily computed directly from input images. The inverse problem of reconstructing a 2D curve from the shaping constraints is solved by a method using curvature shaping, in which the 2D image space is used in conjunction with its curvature space to generate the curve dynamically. The solution allows curve length to be determined and used subsequently for curve modeling using polynomial basis functions. Polynomial basis functions of high orders are shown to be necessary to incorporate perceptual information commonly available at the biological visual front-end.