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A Background Segmentation and Feature Point Extraction Method of Human Motion Recognition

In this paper, we propose a novel background segmentation and feature point extraction method of a human motion for the augmented reality game. First, our method transforms input image from RGB color space to HSV color space, then segments a skin colored area using double threshold of H, S value. And it also segments a moving area using the time difference images and then removes the noise of the area using the Hessian affine region detector. The skin colored area with the moving area is segmented as a human motion. Next, the feature points for the human motion are extracted by calculating the center point for each block in the previously obtained image. The experiments on various input images show that our method is capable of correct background segmentation and feature points extraction 12 frames per second.