Spline curve matching with sparse knot sets: applications to deformable shape detection and recognition

Splines can be used to approximate noisy data with a few control points. This paper presents a new curve matching method for deformable shapes using two-dimensional splines. In contrast to the residual error criterion [F.S. Cohen et al., 1992], which is based on relative locations of corresponding knot points such that is reliable primarily for dense point sets, we use deformation energy of thin-plate-spline mapping between sparse knot points and normalized local curvature information. This method has been tested successfully for the detection and recognition of deformable shapes.