Hand image segmentation using sequential-image-based hierarchical adaptation

Two methods to extract a moving target region from a series of images are presented. Pixel value distributions for both the target object and background region are estimated for each pixel with roughly extracted moving regions. Using the distributions, stable target extraction is performed. In the first method, the distributions are approximated with Gaussian distribution functions and the probability of a pixel being associated with the target object is calculated. In the second method, a Markov random field model is applied to perform region segmentation on regularized input images using the estimated pixel value distributions. The texture parameters for the target object region can be calculated from the estimated pixel value distributions. Experimental results obtained by these two methods using hand motion images are presented.