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Monocular Vision Gesture Segmentation Based on Skin Color and Motion Detection
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    Abstract:

    A kind of gesture segmentation method based on monocular vision was built for the analysis of the skin color information characteristics and gesture movements features, with which a meaningful gesture region could be obtained from the video image sequence. For the identified background image, the skin color region of gestures was captured through the analysis of the skin color information characteristics with a sampling interval of 10 frames. At the same time, the movement region of gestures was captured through the difference method, and then the initial gesture region could be obtained after the fusion of the skin color region and the movement region. The erosion and dilation algorithm of mathematical morphology were further studied, and the gestures segmentation and positioning of the video image sequence were realized. The experiment results have shown that the method has a good gesture segmentation results and higher positioning accuracy.

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