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Evaluating Color Representations for On-Line Road Detection
AbstractDetecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most common combinations. The evaluation is done on a set of 7000 road images acquired using an on-board camera in different real-driving situations.
Related Material
[pdf][bibtex]@InProceedings{M._2013_ICCV_Workshops,
author = {Jose M. Alvarez and Theo Gevers and Antonio M. Lopez},
title = {Evaluating Color Representations for On-Line Road Detection},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}
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