Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wu, BF | en_US |
dc.contributor.author | Lin, CT | en_US |
dc.date.accessioned | 2014-12-08T15:25:21Z | - |
dc.date.available | 2014-12-08T15:25:21Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.isbn | 0-7803-8961-1 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/17731 | - |
dc.description.abstract | In this paper, the obstacle detection for autonomous vehicle is carried out by a monocular camera, which is capable of detecting multiple obstacles, identifying the difference between obstacles and text or shadows on the road surface The task of detection can be fulfilled under the circumstances of general brightness or in the presence of strong sunshine. An obstacle detection approach named Contour Size.Similarity (CSS) is developed in this paper. CSS is a way to make use of, the contour size of objects, and compare the similarity between objects and obstacles detected by means of fuzzy so as to judge whether the objects in the images are the obstacles we want to detect. The I.obstacles in this paper mainly refer to vehicles. Vehicles and obstacles with similar contour of vehicles can be detected by CSS. Then, we use section division to find out the nearest obstacle in separate section to provide necessary information for autonomous vehicles. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | obstacle detection | en_US |
dc.subject | image | en_US |
dc.subject | vision-based | en_US |
dc.subject | autonomous vehicles | en_US |
dc.title | A fuzzy vehicle detection based on contour size similarity | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2005 IEEE INTELLIGENT VEHICLES SYMPOSIUM PROCEEDINGS | en_US |
dc.citation.spage | 496 | en_US |
dc.citation.epage | 501 | en_US |
dc.contributor.department | 電控工程研究所 | zh_TW |
dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
dc.identifier.wosnumber | WOS:000235518700083 | - |
Appears in Collections: | Conferences Paper |