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dc.contributor.authorLai, CCen_US
dc.contributor.authorTsai, WHen_US
dc.date.accessioned2014-12-08T15:46:45Z-
dc.date.available2014-12-08T15:46:45Z-
dc.date.issued1999-04-01en_US
dc.identifier.issn0736-5845en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0736-5845(99)00006-Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/31440-
dc.description.abstractan approach to the estimation of moving lateral vehicle locations for driving assistance using wheel shape information in single 2-D vehicle images by 3-D computer vision techniques is proposed. The location scheme is supposed to be performed on a vehicle with a camera mounted on the front bumper. An analytical solution is applied to estimate locations of the lateral vehicle. Firstly, the rear wheel shape of a lateral vehicle moving in a nearby lane is imaged. By using the Hough transform, the projected wheel shape, which is an ellipse, is detected. Secondly. the equation of the detected ellipse is used to infer the orientation angle of the lateral vehicle with respect to the camera view direction. Finally, the center of the ellipse shape is used to determine the relative position of the lateral vehicle with respect to the camera lens center, Moreover, an edge-point verification algorithm is utilized to extract the ellipse shape more precisely in the image processing stage. Both computer simulated and real images are tested and good experimental results show the effectiveness of the proposed approach for estimating lateral vehicle locations. The results are useful for driving assistance and vehicle collision avoidance and are discussed in detail. (C) 1999 Elsevier Science Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectestimation of lateral vehicle locationen_US
dc.subjectdriving assistanceen_US
dc.subjectvehicle avoidanceen_US
dc.subjectwheel shapeen_US
dc.subjectellipse detectionen_US
dc.subjectcomputer visionen_US
dc.titleEstimation of moving vehicle locations using wheel shape information in single 2-D lateral vehicle images by 3-D computer vision techniquesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0736-5845(99)00006-Xen_US
dc.identifier.journalROBOTICS AND COMPUTER-INTEGRATED MANUFACTURINGen_US
dc.citation.volume15en_US
dc.citation.issue2en_US
dc.citation.spage111en_US
dc.citation.epage120en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000081086700002-
dc.citation.woscount4-
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