1. A process for segmenting an image of an image sequence, comprising the process actions of: (a) designating foreground regions in an initial image of an image sequence; (b) defining certain regions of the initial image as foreground and certain regions of the initial image as background based on the designated foreground regions; (c) learning a foreground spatial-color Gaussian Mixture Model (SCGMM) model which describes the foreground regions and background SCGMM model that describes the background regions of the initial image; (d) segmenting the initial image using a graph cut procedure which minimizes a Markov random field energy function containing the learned foreground and background SCGMM models; (e) inputting a next image of the image sequence; (f) updating the foreground and background SCGMM models using a joint SCGMM tracking procedure; and (g) performing a graph cut procedure which minimizes a Markov Random Field energy function containing the updated foreground and background SCGMM models to segment the next image of the sequence; and (h) updating each of the foreground and background SCGMM models with the segmented result of process action (g).