Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Chung-Hee | - |
dc.contributor.author | Lim, Young-Chul | - |
dc.contributor.author | Kim, Dongyoung | - |
dc.contributor.author | Sohng, Kyu-Ik | - |
dc.date.available | 2017-07-11T06:29:03Z | - |
dc.date.created | 2017-04-10 | - |
dc.date.issued | 2014-11 | - |
dc.identifier.issn | 1392-1215 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/3147 | - |
dc.description.abstract | Despite significant progress in vehicle detection over the last few decades, vehicle detection performance in heavy traffic is still inadequate. In this paper, we propose a new algorithm for vehicle detection in heavy traffic to improve detection performance. It uses two proposed segmentation methods, namely, the disparity map-based bird's-eye-view mapping segmentation method and the edge distance weighted conditional random field (CRF)-based segmentation method. Our experimental results show that the proposed algorithm outperforms conventional algorithms. The improvements in performance range from 10.8 % to 20.5 % increase in F-measure. | - |
dc.language | English | - |
dc.publisher | Kauno Technologijos Universitetas | - |
dc.title | Improved Vehicle Detection Algorithm in Heavy Traffic for Intelligent Vehicle | - |
dc.type | Article | - |
dc.identifier.doi | 10.5755/j01.eee.20.9.3734 | - |
dc.identifier.scopusid | 2-s2.0-84911437121 | - |
dc.identifier.bibliographicCitation | Elektronika ir Elektrotechnika, v.20, no.9, pp.54 - 58 | - |
dc.description.isOpenAccess | FALSE | - |
dc.subject.keywordAuthor | Intelligent vehicle | - |
dc.subject.keywordAuthor | image segmentation | - |
dc.subject.keywordAuthor | object recognition | - |
dc.subject.keywordAuthor | stereo image processing | - |
dc.citation.endPage | 58 | - |
dc.citation.number | 9 | - |
dc.citation.startPage | 54 | - |
dc.citation.title | Elektronika ir Elektrotechnika | - |
dc.citation.volume | 20 | - |
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