Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images
Madden, Michael G.
Munroe, Daniel T.
MetadataShow full item record
This item's downloads: 695 (view details)
"Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images", Daniel Munroe and Michael G. Madden. Proceedings of AICS-05: Irish Conference on Artificial Intelligence and Cognitive Science, Portstewart, Sept 2005.
This paper investigates the use of machine learning classification techniques applied to the task of recognising the make and model of vehicles. Although a number of vehicle classification systems already exist, most of them seek only to distinguish between vehicle categories, e.g. identifying whether a vehicle is a bus, truck or car. The system presented here demonstrates that a set of features extracted from the frontal view of a vehicle may be used to determine the vehicle type (make and model) with high accuracy. The performance of some standard multi-class classification algorithms is compared for this problem. A one-class k-Nearest Neighbour classification algorithm is also implemented and tested.