Implementation and Validation of the Shape Context Descriptor
by Juan Manuel Perez Rua for Open Source Computer Vision Library (OpenCV)
The Shape Context descriptor was proposed by Serge Belongie and Jitendra Malik in 2000. This feature is a histogram based shape descriptor and includes an approach for point correspondence. This tool is naturally invariant to translation, small perturbations, and can be adapted to be rotation invariant, and more. These characteristics had been shown with a test framework based on known databases benchmarks. This is why I think Shape Context is a valuable contribution to OpenCV. However, this implementation should be done along with optimal histogram distance like EMD, and a classical shape comparison approach as the Hausdorff distance, in order to add a complete and robust shape descriptor/comparison tools to OpenCV. Implementations must be proved to work with the same database bench-marking used in the state of the art.