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dc.contributor.authorPryor, Gallagher D.
dc.contributor.authorRehman, Tauseef ur
dc.contributor.authorLankton, Shawn
dc.contributor.authorVela, Patricio A.
dc.contributor.authorTannenbaum, Allen R.
dc.date.accessioned2009-08-24T20:02:17Z
dc.date.available2009-08-24T20:02:17Z
dc.date.issued2007-12
dc.identifier.citationGallagher Pryor, Tauseef ur Rehman, Shawn Lankton, Patricio A. Vela and Allen Tannenbaum, Fast Optimal Mass Transport for Dynamic Active Contour Tracking on the GPU, 46th IEEE Conference on Decision and Control, 2007, 2681-2688en
dc.identifier.isbn978-1-4244-1497-0
dc.identifier.issn0191-2216
dc.identifier.urihttp://hdl.handle.net/1853/29597
dc.description©2007 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
dc.descriptionPresented at the 46th IEEE Conference on Decision and Control, New Orleans, Louisiana USA, December 12-14, 2007.
dc.descriptionDOI: 10.1109/CDC.2007.4434996
dc.description.abstractIn computational vision, visual tracking remains one of the most challenging problems due to noise, clutter, occlusion, and dynamic scenes. No one technique has yet managed to solve this problem completely, but those that employ control- theoretic filtering techniques have proven to be quite successful. In this work, we extend one such technique by Niethammer et al. in which implicitly represented dynamically evolving contours are filtered using a geometric observer framework. The effectiveness of the observer hangs upon the solution of two major problems: (1) the calculation of accurate curve velocities and (2) the determination of diffeomorphic correspondence maps between curves for geometric interpolation. We propose the use of novel image registration techniques such as image warping and optimal mass transport for the solution of these problems which increase the performance of the framework and reduce algorithmic complexity. One major drawback to the original scheme, as it relies on PDE solutions, is its computational burden restricting it from real time use. We show that the framework can, in fact, run in near real time by implementing our additions to the framework on the graphics processing unit (GPU) and show better execution times for these algorithms than reported in recent literature.en
dc.language.isoen_USen
dc.publisherGeorgia Institute of Technologyen
dc.subjectComputational complexityen
dc.subjectComputer visionen
dc.subjectCoprocessorsen
dc.subjectEdge detectionen
dc.subjectFiltering theoryen
dc.subjectGeometryen
dc.subjectImage registrationen
dc.subjectInterpolationen
dc.subjectPartial differential equationsen
dc.subjectTrackingen
dc.titleFast Optimal Mass Transport for Dynamic Active Contour Tracking on the GPUen
dc.typeProceedingsen
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineering
dc.publisher.originalInstitute of Electrical and Electronics Engineers


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