Online dictionary learning for car recognition using sparse coding and lars

Abstract

The bag of feature method coupled with online dictionary learning is the basis of our car make and model recognition algorithm. By using a sparse coding computing technique named LARS (Least Angle Regression) we learn a dictionary of codewords over a dataset of Square Mapped Gradient feature vectors obtained from a densely sampled narrow patch of the front part of vehicles. We then apply SVMs (Support Vector Machines) and KMeans supervised classification to obtain some promising results.