Visual detection of vehicles using a bag-of-features approach

Abstract

This paper presents and evaluates the performance of a method for vehicle detection using a bag-of-features methodology. The algorithm combines Speeded Up Robust Features with a Support Vector Machine. An optimization to the bag-of-features dictionary based on a genetic algorithm for attribute selection is also described. The results obtained show that this method can successfully address the problem of vehicle classification.