DocumentCode
2839794
Title
Adaptive road detection through continuous environment learning
Author
Foedisch, Mike ; Takeuchi, Aya
Author_Institution
Div. of Intelligent Syst., Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
fYear
2004
fDate
13-15 Oct. 2004
Firstpage
16
Lastpage
21
Abstract
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.
Keywords
learning (artificial intelligence); neural nets; object detection; road traffic; adaptive road detection; adaptive road feature acquisition; autonomous driving; color histograms; continuous environment learning; neural network; Adaptive systems; Feature extraction; Filters; Histograms; Humans; Intelligent systems; NIST; Neural networks; Real time systems; Roads;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
ISSN
1550-5219
Print_ISBN
0-7695-2250-5
Type
conf
DOI
10.1109/AIPR.2004.9
Filename
1409668
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