Patent ID: 7076473
Filing Date: 2006-07-11
Classification: G06K

Abstract:
1. A computer implemented method for learning a binary classifier for classifying samples into a first class and a second class, comprising the steps of: acquiring a set of training samples from a physical system, each training sample labeled as either belonging to the first class of samples of the physical system or to the second class of samples of the physical system; connecting pairs of dyadic samples by projection vectors, a first sample of each dyadic pair belonging to the first class and a second sample of each dyadic pair belonging to the second class; forming a set of hyperplanes having a surface normal to the projection vectors; selecting one hyperplane from the set of hyperplanes, the selected hyperplane minimizing a weighted classification error; weighting the set of training samples according to a classification by the selected hyperplane; combining the selected hyperplanes into a binary classifier; and repeating the selecting, weighting, and combining a predetermined number of iterations to obtain a final classifier for classifying test samples of the physical system into the first and second classes of the physical system.