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Improving hand posture recognition performance using multi-modalities

Hand gesture recognition has been researched for a long time. However, performance of such methods in practical application still has to face with many challenges due to the variation of hand pose, hand shape, viewpoints, complex background, light illumination or subject style. In this work, we deeply investigate hand representations on various extractors from independent data (such as RGB image and Depth image). |