Robust Hand Gesture Recognition with Feature Selection and Hierarchical Temporal Self-Similarities
Keywords:
Self-similarity matrix, feature selection, HOG feature, kinect IAbstract
There are increasing numbers of hand interaction
system based on Microsoft Kinect for its providing the extra
depth information which facilitates the hand segmentation.
However, most of the recent papers focus on the stable hand
recognition whose assumption can hardly be fulfilled in highly
interactive HCI environment. We proposed a robust method to
recognize both the moving and stable hand. We explored
several features in both RGB and depth images based on a novel
descriptor, and then built a feature selection model to find the
robust features for recognition. Then, we exploited the
hierarchical self-similarity matrix (H-SSM) to detect the
gesture transformation to further enhancing the system
robustness. Our method can be widely used in gesture
recognition and the effectiveness has been verified through
experiment.
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