[Reading] Shape Matching and Object Recognition Using Shape Contexts

This paper propose a robust and simple algorithm for finding correspondences and measure the similarity between shapes and exploit it for object recognition. This approach is a 3-stage process: (1) Find correspondences between points on shapes, (2) Estimate transformation, and (3) Measure similarity. In order to solve the correspondence problem, it propose a descriptor named shape context. Shape context records the distribution of relative positions of points. the estimation use regularized thin plate spline as transformation model. Shape distance is a weighted sum of shape context distance, appearance distance and bending energy. Results are presented for handwritten digits, 3D objects, silhouettes and trademarks.