Title:
Fast incorporation of optical flow into active polygons

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dc.contributor.author Unal, Gozde en_US
dc.contributor.author Krim, Hamid en_US
dc.contributor.author Yezzi, Anthony en_US
dc.contributor.corporatename Siemens Corporate Research. Intelligent Vision and Reasoning Dept. en_US
dc.contributor.corporatename North Carolina State University. Electrical and Computer Engineering Dept. en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering en_US
dc.date.accessioned 2013-09-10T14:37:01Z
dc.date.available 2013-09-10T14:37:01Z
dc.date.issued 2005-06
dc.description ©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. en_US
dc.description DOI: 10.1109/TIP.2005.847286 en_US
dc.description.abstract In this paper, we first reconsider, in a different light, the addition of a prediction step to active contour-based visual tracking using an optical flow and clarify the local computation of the latter along the boundaries of continuous active contours with appropriate regularizers.We subsequently detail our contribution of computing an optical flow-based prediction step directly from the parameters of an active polygon, and of exploiting it in object tracking. This is in contrast to an explicitly separate computation of the optical flow and its ad hoc application. It also provides an inherent regularization effect resulting from integrating measurements along polygon edges. As a result, we completely avoid the need of adding ad hoc regularizing terms to the optical flow computations, and the inevitably arbitrary associated weighting parameters. This direct integration of optical flow into the active polygon framework distinguishes this technique from most previous contour-based approaches, where regularization terms are theoretically, as well as practically, essential. The greater robustness and speed due to a reduced number of parameters of this technique are additional and appealing features. en_US
dc.identifier.citation G. Unal, H. Krim, and A. Yezzi, “Fast incorporation of optical flow into active polygons,” IEEE Transactions on Image Processing, 14 (6), 745-759 (June 2005) en_US
dc.identifier.doi 10.1109/TIP.2005.847286
dc.identifier.issn 1057-7149
dc.identifier.uri http://hdl.handle.net/1853/48921
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers en_US
dc.subject Level-set methods en_US
dc.subject Motion estimation en_US
dc.subject Object tracking en_US
dc.subject Optical flow en_US
dc.subject Polygon evolution en_US
dc.subject Region-based active contour en_US
dc.title Fast incorporation of optical flow into active polygons en_US
dc.type Text
dc.type.genre Article
dspace.entity.type Publication
local.contributor.author Yezzi, Anthony
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
relation.isAuthorOfPublication 53ee63a2-04fd-454f-b094-02a4601962d8
relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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