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dc.contributor.author Lim, Young Chul -
dc.contributor.author Kang, Minsung -
dc.date.available 2017-07-11T07:39:25Z -
dc.date.created 2017-05-08 -
dc.date.issued 2015 -
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.relation.ispartof Research in Adaptive and Convergent Systems, RACS 2015 -
dc.title Pyramidal channel features for pedestrian detector -
dc.type Conference Paper -
dc.identifier.doi 10.1145/2811411.2811511 -
dc.identifier.scopusid 2-s2.0-84960899990 -
dc.identifier.bibliographicCitation Research in Adaptive and Convergent Systems, RACS 2015, pp.195 - 199 -
dc.citation.conferenceDate 2015-10-09 -
dc.citation.conferencePlace US -
dc.citation.endPage 199 -
dc.citation.startPage 195 -
dc.citation.title Research in Adaptive and Convergent Systems, RACS 2015 -
dc.type.docType Conference Paper -
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Division of Automotive Technology 2. Conference Papers

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