4. The method according to claim 1 , wherein the method further comprises a step of setting up a plurality of learning machines so that each learning machine represents an auxiliary demographics class, whereby the auxiliary demographics class comprises facial images having the same gender and ethnicity classes.
1. A method for determining age categories of people, comprising the following steps of: a) annotating a facial image database according to the demographics classes of the individual face, b) training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) detecting and tracking a facial image from the input image frame, d) processing said facial image to extract image features, and e) processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the method further comprises a step of determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold.