Fast pattern classification based on a sparse transform

Abstract

Techniques for determining a feature in an image or soundtrack of one or more dimensions include receiving a subject image. A sparse transformed subject image is determined, which represents the subject image with a few significant coefficients compared to a number of values in the subject image. Multiple patch functions are received, which are based on a portion of a sparse transformed image for each of a training set of images and which represent learned features in the training set. A feature is determined to be in the subject image based on the transformed subject image and the plurality of patch functions. In various embodiments, a wavelet transformation or audio spectrogram is performed to produce the sparse transformed images. In some embodiments, the feature in the subject is determined regardless of feature location or size or orientation in the subject image.