The present invention provides for a method for tracking a number of objects or object parts in image sequences, comprising following a Bayesian-like approach to object tracking, computing, at each time a new image is available, a probability distribution over all possible target configurations for that time, said Bayesian-like approach to object tracking comprising the following steps: - Prediction step: a probability distribution is computed for the previous image, at time (t-1), is propagated to the new image at time (t) according to a probabilistic model of target dynamics, obtaining a predicted distribution at time (t) ; - Update step: the predicted distribution at time (t) is then aligned with the evidence contained in the new image at time (t) according to a probabilistic model of visual likelihood.