Patent ID: 7899253
Filing Date: 2011-03-01
Classification: G06K

Abstract:
1. A computer implemented method for constructing a classifier from training data and detecting moving objects in test data using the classifier, comprising the steps of: generating high-level features from low-level features extracted from training data, the high-level features being positive definite matrices in a form of an analytical manifold; selecting a subset of the high-level features; determining an intrinsic mean matrix from the subset of the selected high-level features; mapping each high-level feature to a feature vector onto a tangent space of the analytical manifold using the intrinsic mean matrix; training an untrained classifier with the feature vectors to obtain a trained classifier; generating test high-level features from test low-level features extracted from test data, the test high-level features being the positive definite matrices in the form of the analytical manifold, in which the training and test data are in a form of images, and wherein the low-level features are derived from pixel intensities, and the high-level features are covariance matrices generated from the pixel intensities features; and classifying the test high-level features using the trained classifier to detect moving objects in the test data.