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dc.contributor.authorJyh-Yeong Changen_US
dc.contributor.authorChien-Wen Choen_US
dc.date.accessioned2014-12-08T15:24:47Z-
dc.date.available2014-12-08T15:24:47Z-
dc.date.issued2006en_US
dc.identifier.isbn978-1-4244-0099-7en_US
dc.identifier.issn1062-922Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/17226-
dc.identifier.urihttp://dx.doi.org/10.1109/ICSMC.2006.385164en_US
dc.description.abstractVision-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 [1], 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.en_US
dc.language.isoen_USen_US
dc.titleVision-based front vehicle detection and its distance estimationen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/ICSMC.2006.385164en_US
dc.identifier.journal2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGSen_US
dc.citation.spage2063en_US
dc.citation.epage2068en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000248078502047-
Appears in Collections:Conferences Paper


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