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Automatic make and model recognition from frontal images of cars

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2 Author(s)
Pearce, G. ; Dept. of Comput. Sci., Univ. of York, York, UK ; Pears, N.

We investigate a range of solutions in car `make and model' recognition. Several different feature detection approaches are investigated and applied to the problem including a new approach based on Harris corner strengths. This approach recursively partitions the image into quadrants, the feature strengths in these quadrants are then summed and locally normalised in a recursive, hierarchical fashion. Two different classification approaches are investigated; a k-nearest-neighbour classifier and a Naive Bayes classifier. Our system is able to classify vehicles with 96.0% accuracy, tested using leave-one-out cross-validation on a realistic dataset of 262 frontal images of cars.

Published in:

Advanced Video and Signal-Based Surveillance (AVSS), 2011 8th IEEE International Conference on

Date of Conference:

Aug. 30 2011-Sept. 2 2011