1. A method of detecting and tracking human faces across a sequence of video frames, said method comprising the steps of: (a) forming a 3D pixel data block from said sequence of video frames; (b) segmenting said 3D data block into a set of 3D segments using 3D spatiotemporal segmentation; (c) forming 2D segments from an intersection of said 3D segments with a view plane, each 2D segment being associated with one 3D segment; (d) in at least one of said 2D segments, extracting features and grouping said features into one or more groups of features; (e) for each group of features, computing a probability that said group of features represents human facial features based on the similarity of the geometry of said group of features with the geometry of a human face model; (f) matching at least one group of features with a group of features in a previous 2D segment and computing an accumulated probability that said group of features represents human facial features using probabilities of matched groups of features; (g) classifying each 2D segment as a face segment or a non-face segment based on said accumulated probability of at least one group of features in each of said 2D segments; and (h) tracking said human faces by finding an intersection of 3D segments associated with said face segments with at least subsequent view planes.