Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2004.1334362
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dc.titleKernel-based method for tracking objects with rotation and translation
dc.contributor.authorZhang, H.
dc.contributor.authorHUANG ZHIYONG
dc.contributor.authorHuang, W.
dc.contributor.authorLi, L.
dc.date.accessioned2013-07-04T07:53:24Z
dc.date.available2013-07-04T07:53:24Z
dc.date.issued2004
dc.identifier.citationZhang, H., HUANG ZHIYONG, Huang, W., Li, L. (2004). Kernel-based method for tracking objects with rotation and translation. Proceedings - International Conference on Pattern Recognition 2 : 728-731. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2004.1334362
dc.identifier.isbn0769521282
dc.identifier.issn10514651
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39955
dc.description.abstractThis paper addresses the issue of tracking translation and rotation simultaneously. Starting with a kernel-based spatial-spectral model for object representation, we define an l 2-norm similarity measure between the target object and the observation, and derive a new formulation to the tracking of translational and rotational object. Based on the tracking formulation, an iterative procedure is proposed. We also develop an adaptive kernel model to cope with varying appearance. Experimental results are presented for both synthetic data and real-world traffic video.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICPR.2004.1334362
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/ICPR.2004.1334362
dc.description.sourcetitleProceedings - International Conference on Pattern Recognition
dc.description.volume2
dc.description.page728-731
dc.description.codenPICRE
dc.identifier.isiut000223877400178
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