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dc.contributor.author Lim, Young Chul ko
dc.contributor.author Kang, Minsung ko
dc.date.available 2017-07-11T07:39:25Z -
dc.date.created 2017-05-08 -
dc.date.issued 2015 -
dc.identifier.citation Research in Adaptive and Convergent Systems, RACS 2015, pp.195 - 199 -
dc.identifier.isbn 9780000000000 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/3701 -
dc.description.abstract Most state-of-the-art pedestrian detectors diversify features to improve the detection performance. Among such features, the gradient histogram is the most informative. This work investigates how diverse orientation information influences the pedestrian detection performance. In this paper, we propose a pedestrian detection method which uses pyramidal aggregated channel features which are generated with a layer-by-layer assembly scheme. Experimental results on the INRIA dataset show that our method can reach state-of-the-art performance despite using only gradient features. © 2015 ACM. -
dc.publisher Association for Computing Machinery, Inc -
dc.title Pyramidal channel features for pedestrian detector -
dc.type Conference -
dc.identifier.doi 10.1145/2811411.2811511 -
dc.identifier.scopusid 2-s2.0-84960899990 -
dc.type.rims CONF -
dc.identifier.citationStartPage 195 -
dc.identifier.citationEndPage 199 -
dc.identifier.citationTitle Research in Adaptive and Convergent Systems, RACS 2015 -
dc.type.journalArticle Conference Paper -
dc.identifier.conferencecountry US -
dc.contributor.affiliatedAuthor Lim, Young Chul -
dc.contributor.affiliatedAuthor Kang, Minsung -
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Convergence Research Center for Future Automotive Technology 2. Conference Papers

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