Patent ID: 7965886

Claim:
A method for detecting multi-view/multi-pose objects, each object having at least one feature, comprising the steps of: (a) receiving a data set of training samples, said samples including images having at least one object; (b) randomly selecting a subset of positive samples from the training samples to create a set of candidate exemplars, wherein said positive samples comprise images of the object to be detected; (c) generating at least one weak classifier from the set of candidate exemplar, each said weak classifier being associated with a position of the selected positive training samples; said position comprising a view, a pose, or combinations thereof; (d) training the weak classifiers based on distance values between at least one feature of each of the candidate exemplar and the corresponding at least one feature of the training sample, wherein said training the weak classifiers comprising segmenting said candidate exemplar into a number of grid cell image regions, computing a gradient orientation histogram for at least one of said grid cell image regions of said candidate exemplar, computing said gradient orientation histogram for all of the training samples and calculating said distance value between the gradient orientation histogram for said at least one of the grid cell image regions of said candidate exemplar and the gradient orientation histogram for all the training samples; (e) computing error rates of each of the trained weak classifiers; and (f) selecting the trained weak classifier with a lowest error rate as the individual classifier; (g) repeating steps (a) through (g) until all the trained weak classifiers have been selected; and (h) automatically combining the individual classifiers into a final classifier, wherein said final classifier is the object to be detected.