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Adaptive unstructured road detection using close range stereo vision
Date
2013-06-26
Author
ÖZÜTEMİZ, Kadri Bugra
Hacinecipoglu, AKİF
Koku, Ahmet Buğra
Konukseven, Erhan İlhan
Metadata
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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.
Subject Keywords
Road detection
,
Stereo vision
,
Unstructured roads
,
Traversibility
,
Continuous learning
,
Near-to-far learning
URI
https://hdl.handle.net/11511/36471
DOI
https://doi.org/10.1109/ascc.2013.6606352
Collections
Department of Mechanical Engineering, Conference / Seminar
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K. B. ÖZÜTEMİZ, A. Hacinecipoglu, A. B. Koku, and E. İ. Konukseven, “Adaptive unstructured road detection using close range stereo vision,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36471.