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A collection of algorithms for use with RGB-D data.
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adithyaprem/pyKinectTools
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pyKinectTools Author: Colin Lea These instructions are sparse and likely to change. If you would like to use this code the best thing is to email me ([email protected]). I am happy to help ---Dependencies--- numpy, scipy, scikit-learn, scikit-image, visvis, opencv ---Installation instructions--- ** Python data libraries: If you use a python virtual environment: pip install numpy scipy matplotlib ipython scikit-learn scikit-image pyside visvis ** OpenCV (Only used for Optical Flow in Histogram of Oriented Optical Flow -- I'm trying to get rid of this dependence!) If on OSX/Ubuntu(12.04+)/Windows see: https://docs.google.com/document/d/1TsPRI1g_iXQmsCs1VPkLm-9M0T1n724H-wAo7QSNpMY/edit Otherwise build from source ---Algorithms--- Background subtraction: Adaptive Mixture of Gaussian, Static median/mean model Feature extraction: Histogram of Oriented Optical Flow, Cuboids, Geodesic Extrema Simple person tracking Basic graph Algorithms Belief Propagation (tree-based) Iterative Closest Point Laplacian Eigenmaps manifolds PCA-based gesture recognition Superpixels wrapper [deprecated -- use the one in skimage instead] Others... Recording with Kinect: Data capture program Video/Skeleton data player (w/ user controller) Depth image utilities (e.g. converting from depth->pointcloud) chalearn annotated dataset reader
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