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Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPR.2005.65
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dc.titleAffine object tracking with kernel-based spatial-color representation
dc.contributor.authorZhang, H.
dc.contributor.authorHuang, W.
dc.contributor.authorHUANG ZHIYONG
dc.contributor.authorLi, L.
dc.date.accessioned2013-07-04T08:17:53Z
dc.date.available2013-07-04T08:17:53Z
dc.date.issued2005
dc.identifier.citationZhang, H., Huang, W., HUANG ZHIYONG, Li, L. (2005). Affine object tracking with kernel-based spatial-color representation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1 : 293-300. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPR.2005.65
dc.identifier.isbn0769523722
dc.identifier.issn10636919
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41025
dc.description.abstractThis paper presents a new visual tracking method that can achieve accurate estimation of affine transformation and precise spatial-color representation. The estimation of transformation provides more information than translation for better motion understanding and also helps maintain the precise representation; the precise representation enables tracking objects in highly-cluttered environment. The basis of the method is a kernel-based similarity measure called affine matching that describes the relationship between image regions with respect to affine transformation parameters. Based on the similarity measure, a mathematical solution is derived for estimating the transformation parameters for moving objects in videos. Various experiments have yielded positive results. © 2005 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CVPR.2005.65
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/CVPR.2005.65
dc.description.sourcetitleProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
dc.description.volume1
dc.description.page293-300
dc.description.codenPIVRE
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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