View : 41 Download: 0

Full metadata record

DC FieldValueLanguage
dc.contributor.author강제원-
dc.date.accessioned2017-08-28T08:05:21Z-
dc.date.available2017-08-28T08:05:21Z-
dc.date.issued2016-
dc.identifier.issn1047-3203-
dc.identifier.issn1095-9076-
dc.identifier.urihttp://dspace.ewha.ac.kr/handle/2015.oak/217931-
dc.description.abstractA compressed domain video saliency detection algorithm, which employs global and local spatiotemporal (GLST) features, is proposed in this work. We first conduct partial decoding of a compressed video bit-stream to obtain motion vectors and DCT coefficients, from which GLST features are extracted. More specifically, we extract the spatial features of rarity, compactness, and center prior from DC coefficients by investigating the global color distribution in a frame. We also extract the spatial feature of texture contrast from AC coefficients to identify regions, whose local textures are distinct from those of neighboring regions. Moreover, we use the temporal features of motion intensity and motion contrast to detect visually important motions. Then, we generate spatial and temporal saliency maps, respectively, by linearly combining the spatial features and the temporal features. Finally, we fuse the two saliency maps into a spatiotemporal saliency map adaptively by comparing the robustness of the spatial features with that of the temporal features. Experimental results demonstrate that the proposed algorithm provides excellent saliency detection performance, while requiring low complexity and thus performing the detection in real-time. (C) 2015 Elsevier Inc. All rights reserved.-
dc.languageEnglish-
dc.publisherACADEMIC PRESS INC ELSEVIER SCIENCE-
dc.subjectVideo saliency detection-
dc.subjectSpatiotemporal feature-
dc.subjectCompressed domain-
dc.subjectVisual attention-
dc.subjectPartial decoding-
dc.subjectImage understanding-
dc.subjectImage analysis-
dc.subjectMotion analysis-
dc.titleCompressed domain video saliency detection using global and local spatiotemporal features-
dc.typeArticle-
dc.relation.volume35-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage169-
dc.relation.lastpage183-
dc.relation.journaltitleJOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION-
dc.identifier.doi10.1016/j.jvcir.2015.12.011-
dc.identifier.wosidWOS:000369879600015-
dc.identifier.scopusid2-s2.0-84952905942-
dc.author.googleLee, Se-Ho-
dc.author.googleKang, Je-Won-
dc.author.googleKim, Chang-Su-
dc.contributor.scopusid강제원(56367466400)-
dc.date.modifydate20170922131342-
Appears in Collections:
엘텍공과대학 > 전자공학과 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE