Shape Context: A New Descriptor for Shape Matching and Object Recognition

Belongie, Serge, Malik, Jitendra, Puzicha, Jan

Neural Information Processing Systems 

We develop an approach to object recognition based on matching shapesand using a resulting measure of similarity in a nearest neighbor classifier. The key algorithmic problem here is that of finding pointwise correspondences between an image shape and a stored prototype shape. We introduce a new shape descriptor, the shape context, which makes this possible, using a simple and robust algorithm. We demonstrate that shape contexts greatly simplify recovery of correspondences between points of two given shapes. Once shapes are aligned, shape contexts are used to define a robust score for measuring shape similarity.

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