Patent ID: 7657102

Claim:
A system for automatically decomposing an image sequence, comprising a computer-readable storage medium storing a program that when executed causes: a computer to perform the following process actions, providing an image sequence of at least one image frame of a scene; providing only a preferred number of classes of objects to be identified within the image sequence; automatically decomposing the image sequence into the preferred number of classes of objects, using probabilistic inference and learning to compute a single set of model parameters comprising a mean visual appearance and variance of each class in the image sequence, processing the provided image sequence and computing the single set of model parameters at a substantially same time that the image sequence is provided, wherein automatically decomposing the image sequence into the preferred number of object classes comprises performing a probabilistic variational expectation-maximization analysis, comprising: forming a probabilistic model having variational parameters representing posterior distributions; initializing said probabilistic model; inputting an image frame from the image sequence; computing a posterior given observed data in said image sequence; and using the posterior of the observed data to update the probabilistic model parameters.