Vehicle type classification from laser scanner profiles: A benchmark of feature descriptors

Abstract

This article targets the problem of vehicle classification using laser scanner profiles, which is usually found as a component of electronic tolling systems. Laser scanners obtain a 3D measurement of the vehicle surface. Previous approaches have extracted high-level features (such as width, height, length and other measurements) from the scanner profiles, or have taken the raw profiles for further pattern analysis. In this article, we focus on feature descriptors for supervised classification of laser scanner profiles. We evaluate a number of feature descriptors, including high-level features and raw profiles, but also introduce new descriptors. A 3D profile when interpreted as a 2D image with depth values as pixel intensities can benefit from recent advances in computer vision. Experiments on a real-world vehicle classification task indicate that the image-based descriptors, especially the Fisher vector, obtain improved performances with respect to high-level features and raw profiles.