%0 Journal Article %A Reza Hassanpour and Asadollah Shahbahrami and Stephan Wong %D 2008 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 17, 2008 %T Adaptive Gaussian Mixture Model for Skin Color Segmentation %U https://publications.waset.org/pdf/4014 %V 17 %X Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions. %P 1348 - 1353