Adaptive unstructured road detection using close range stereo vision

Detection of road regions is not a trivial problem especially in unstructured and/or off-road domains since traversable regions of these environments do not have common properties unlike urban roads or highways. In this paper a novel unstructured road detection algorithm that can continuously learn...

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Bibliographic Details
Published in2013 9th Asian Control Conference (ASCC) pp. 1 - 6
Main Authors Ozutemiz, Kadri Bugra, Hacinecipoglu, Akif, Koku, A. Bugra, Konukseven, Erhan Ilhan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2013
Subjects
Adaptation models
Cameras
Classification algorithms
continuous learning
Image color analysis
Libraries
near-to-far learning
road detection
Roads
stereo vision
Training
traversibility
unstructured roads
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Summary:Detection of road regions is not a trivial problem especially in unstructured and/or off-road domains since traversable regions of these environments do not have common properties unlike urban roads or highways. In this paper a novel unstructured road detection algorithm that can continuously learn the road region is proposed. The algorithm gathers close-range stereovision data and uses this information to estimate the long-range road region. The experiments show that the algorithm gives satisfactory results even under changing light conditions.
ISBN:9781467357678
1467357677
DOI:10.1109/ASCC.2013.6606352