Abstract: | superellipses are parametric models that can be used for representing two dimensional object parts or aspects of 3-D parts. Previously little care was given to obtaining a precise sampling of the contour of these models. Equal-distance sampling of superellipse model contours is, however, important for rendering and in cases in which a cost function needs to be estimated for data fitting or parameter estimation, such as in model-based optimisation. In this paper we present a new parametric method for achieving equal-distance sampling of superellipse model contours that properly combines two simple first order models of the sampled points distance function.
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