3. The method of claim 1 wherein the training stage comprises a semi-supervised training stage wherein at least one human pose in the set of training images is manually labeled and at least one human pose in the set of training images is unlabeled.
1. A method for human detection and a pose classification comprising: using a computer to perform the steps of: receiving a probabilistic model derived from a set of training images in at least one of an unsupervised training stage or a semi-supervised training stage; generating a set of test image descriptors representing a test image; determining a likelihood that the test image contains a human based on parameters of the probabilistic model and the test image descriptors; and classifying a body pose of a detected human in the test image based on the test image descriptors and the parameters of the probabilistic model.