Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Min-Sung | - |
dc.contributor.author | Lim, Young-Chul | - |
dc.date.available | 2017-07-11T07:41:41Z | - |
dc.date.created | 2017-05-08 | - |
dc.date.issued | 2015 | - |
dc.identifier.isbn | 9780000000000 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/3723 | - |
dc.description.abstract | In this paper, we present a multiple hypotheses framework to detect pedestrians accurately and precisely. The multiple hypotheses framework consists of obstacle detection, pedestrian recognition and data association. Obstacle detection detects all obstacles on the road. Pedestrian recognition classifies the detected obstacles as persons or non-persons. The data association component assigns multiple results to the correct hypotheses with multiple similarity functions. The experimental results demonstrate that the proposed method enhances the accuracy and precision of the region of interest. © 2015 ACM. | - |
dc.publisher | Association for Computing Machinery, Inc | - |
dc.relation.ispartof | Research in Adaptive and Convergent Systems, RACS 2015 | - |
dc.title | Fast stereo-based pedestrian detection using hypotheses | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.1145/2811411.2811486 | - |
dc.identifier.scopusid | 2-s2.0-84960857316 | - |
dc.identifier.bibliographicCitation | Research in Adaptive and Convergent Systems, RACS 2015, pp.131 - 135 | - |
dc.citation.conferenceDate | 2015-10-09 | - |
dc.citation.conferencePlace | US | - |
dc.citation.endPage | 135 | - |
dc.citation.startPage | 131 | - |
dc.citation.title | Research in Adaptive and Convergent Systems, RACS 2015 | - |
dc.type.docType | Conference Paper | - |
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