![]() They have been shown to outperform existing features such as SIFT and spin images for RGB-D object recognition. Kernel Descriptors are a family of features for extracting rich cues from RGB-D data. ![]() It achieves state-of-the-art results on the RGB-D Object Dataset. ![]() Code for HMP features now available here. Hierarchical Matching Pursuit (HMP) is an unsupervised feature learning technique for RGB, depth, and 3D point cloud data. Hierarchical Matching Pursuit Features (Matlab) If you have any suggestions or would like to contribute software to this page, please contact Kevin Lai. In this page we include some code snippets and software for processing the data.
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