Title :
Vehicle type classification from laser scans with global alignment kernels
Author :
Chidlovskii, Boris ; Csurka, Gabriela ; Rodriguez-Serrano, Jose
Author_Institution :
Xerox Res. Centre Eur., Meylan, France
Abstract :
This paper addresses 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 treated the laser scans as images. In addition to high-level features (such as width, height, length and other measurements) from the scanner profiles, feature descriptors have been used for supervised classification of laser scanner profiles. This allowed to deploy a generic approach to the image classification based on Fisher features. In this paper we adopt a different approach which extracts and analyses vehicle shapes from the laser scans. The method proceeds to finding typical vehicle shapes and classifying them through the global shape alignment.
Keywords :
feature extraction; image classification; intelligent transportation systems; optical scanners; road pricing (tolls); road vehicles; shape recognition; traffic engineering computing; 3D measurement; Fisher features; electronic tolling systems; feature descriptors; global alignment kernels; global shape alignment; high-level features; image classification; laser scanner profiles; supervised classification; vehicle shapes extraction; vehicle surface; vehicle type classification; Accuracy; Feature extraction; Kernel; Lasers; Measurement by laser beam; Shape; Vehicles;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/ITSC.2014.6958145