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Adaptive Road Detection through Continuous Environment Learning
Cosmos Club, Washington, DC October 13-October 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AIPR.2004.933rd Applied Imagery Pattern Recognit ...
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Mike Foedisch, National Institute of Standards and Technology, Gaithersburg, MD
Aya Takeuchi, Advanced Technology and Research, Corp., Burtonsville, MD
The Intelligent Systems Division of the National Institute of Standards and Technology has been engaged for several years in developing real-time systems for autonomous driving. A road detection program is an essential part of the project. Previously we developed an adaptive road detection system based on color histograms using a neural network. This, however, still required human involvement during the initialization step. As a continuation of the project, we have expanded the system so that it can adapt to the new environment without any human intervention. This system updates the neural network continuously based on the road image structure. In order to reduce the possibility of misclassifying road and non-road, we have implemented an adaptive road feature acquisition method.
Citation:
Mike Foedisch, Aya Takeuchi, "Adaptive Road Detection through Continuous Environment Learning," aipr, pp.16-21, 33rd Applied Imagery Pattern Recognition Workshop (AIPR'04), 2004
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