To extend the functionalities of Advanced Driver Assistance Systems (ADAS) and have a more accurate control on the parameters of sensors mounted on an intelligent vehicle, a tool that can classify the scenarios which the vehicle moves in, is needed. This article presents a comparison of three classification techniques (PCA, ANN and SVM) to obtain a fast and robust scene classifier based only on images. The systems presented in this paper have been trained on three different categories of traffic scenarios: urban, highway, and rural, on a total of more than 23 hours of driving in different countries.
Document type: Part of book or chapter of book
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Published on 01/01/2013
Volume 2013, 2013
DOI: 10.1007/978-3-642-41181-6_59
Licence: CC BY-NC-SA license
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