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Sim, Jae-Young
Visual Information Processing Lab (VIP Lab)
Research Interests
  • Image processing, computer vision, 3D visual processing, signal processing

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Correspondence matching of multi-view video sequences using mutual information based similarity measure

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dc.contributor.author Lee, Soon-Young ko
dc.contributor.author Sim, Jae-Young ko
dc.contributor.author Kim, Chang-Su ko
dc.contributor.author Lee, Sang-Uk ko
dc.date.available 2014-04-10T02:33:20Z -
dc.date.created 2013-12-09 ko
dc.date.issued 2013-12 ko
dc.identifier.citation IEEE TRANSACTIONS ON MULTIMEDIA, v.15, no.8, pp.1719 - 1731 ko
dc.identifier.issn 1520-9210 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/3958 -
dc.description.abstract We propose a correspondence matching algorithm for multi-view video sequences, which provides reliable performance even when the multiple cameras have significantly different parameters, such as viewing angles and positions. We use an activity vector, which represents the temporal occurrence pattern of moving foreground objects at a pixel position, as an invariant feature for correspondence matching. We first devise a novel similarity measure between activity vectors by considering the joint and individual behavior of the activity vectors. Specifically, we define random variables associated with the activity vectors and measure their similarity using the mutual information between the random variables. Moreover, to find a reliable homography transform between views, we find consistent pixel positions by employing the iterative bidirectional matching. We also refine the matching results of multiple source pixel positions by minimizing a matching cost function based on the Markov random field. Experimental results show that the proposed algorithm provides more accurate and reliable matching performance than the conventional activity-based and feature-based matching algorithms, and therefore can facilitate various applications of visual sensor networks. ko
dc.description.statementofresponsibility close -
dc.language 영어 ko
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC ko
dc.title Correspondence matching of multi-view video sequences using mutual information based similarity measure ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84888381448 ko
dc.identifier.wosid 000327393900001 ko
dc.type.rims ART ko
dc.description.wostc 0 *
dc.description.scopustc 0 *
dc.date.tcdate 2014-10-18 *
dc.date.scptcdate 2014-07-12 *
dc.identifier.doi 10.1109/TMM.2013.2271747 ko
dc.identifier.url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84888381448 ko
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