DocumentCode :
3127313
Title :
Performance evaluation of vision-based lane sensing: some preliminary tools, metrics, and results
Author :
Kluge, Karl C.
Author_Institution :
Artificial Intelligence Lab., Michigan Univ., Ann Arbor, MI, USA
fYear :
1997
fDate :
9-12 Nov 1997
Firstpage :
723
Lastpage :
728
Abstract :
The growth in the number of vision-based lane sensing algorithms in the literature has far outpaced the development of methods for characterizing the limits of performance of such algorithms. The large amounts of data such systems will need to correctly process to be sufficiently reliable for commercial deployment requires that tools be developed for the evaluation process which are almost completely automated. In order to gain some insight into the issues involved, a small pilot study was performed to compare the reliability of two methods used by the YARF road tracking system for locating white painted stripes in small image windows. The evaluation methodology and results are described. In addition, several proposed metrics for measuring road detectability are defined and evaluated
Keywords :
image recognition; mobile robots; road vehicles; robot vision; YARF road tracking system; performance evaluation; reliability; road detectability metrics; small image windows; vision-based lane sensing; white painted stripes; Accidents; Layout; Machine vision; Mobile robots; Performance gain; Roads; Robot vision systems; Software algorithms; System performance; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation System, 1997. ITSC '97., IEEE Conference on
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-4269-0
Type :
conf
DOI :
10.1109/ITSC.1997.660563
Filename :
660563
Link To Document :
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