DocumentCode :
465882
Title :
Vision-Based Front Vehicle Detection and Its Distance Estimation
Author :
Chang, Jyh-Yeong ; Cho, Chien-Wen
Author_Institution :
Nat. Chiao-Tung Univ., Hsin-Chu
Volume :
3
fYear :
2006
fDate :
8-11 Oct. 2006
Firstpage :
2063
Lastpage :
2068
Abstract :
Vision-based driver assistant systems are very promising in Intelligent Transportation System (ITS). This paper will propose a system that can detect front vehicles and estimate the nearest car distance from the host car. In a companion paper, we have developed a scene analysis module that deals with scene segmentation and natural object labeling of forward-looking images by the use of fuzzy adaptive resonance theory (ART) and fuzzy inference techniques. Based on this technique, the proposed system can detect the front vehicles and then estimate the distance of the nearest car from us. The validity of our proposed scheme in car detection and the distance estimation was verified to be very successful by field-test experiments.
Keywords :
adaptive resonance theory; automated highways; fuzzy reasoning; image segmentation; Intelligent Transportation System; car detection; distance estimation; fuzzy adaptive resonance theory; fuzzy inference techniques; scene segmentation; vision-based driver assistant systems; vision-based front vehicle detection; Image analysis; Intelligent transportation systems; Laser radar; Layout; Pixel; Radar detection; Radar imaging; Roads; Subspace constraints; Vehicle detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
Type :
conf
DOI :
10.1109/ICSMC.2006.385164
Filename :
4274170
Link To Document :
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