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Car Type Recognition with Deep Neural Networks
February 23, 2016 Β· Declared Dead Β· π 2016 IEEE Intelligent Vehicles Symposium (IV)
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Authors
Heikki Huttunen, Fatemeh Shokrollahi Yancheshmeh, Ke Chen
arXiv ID
1602.07125
Category
cs.CV: Computer Vision
Citations
88
Venue
2016 IEEE Intelligent Vehicles Symposium (IV)
Last Checked
4 months ago
Abstract
In this paper we study automatic recognition of cars of four types: Bus, Truck, Van and Small car. For this problem we consider two data driven frameworks: a deep neural network and a support vector machine using SIFT features. The accuracy of the methods is validated with a database of over 6500 images, and the resulting prediction accuracy is over 97 %. This clearly exceeds the accuracies of earlier studies that use manually engineered feature extraction pipelines.
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