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dc.contributor.authorMatas, Jiří
dc.contributor.authorŠochman, Jan
dc.date.accessioned2012-06-12T08:39:13Z
dc.date.available2012-06-12T08:39:13Z
dc.date.issued2007-04
dc.identifier.citationJirí Matas and Jan Šochman. Wald's sequential analysis for time-constrained vision problems. In Seth Hutchinson, editor, IEEE International Conference on Robotics and Automation, Workshops and Tutorials, page 10, Piscataway, USA, April 2007. IEEE, IEEE. CDROM, invited paper.cze
dc.identifier.urihttp://hdl.handle.net/10467/9541
dc.description.abstractIn detection and matching problems in computer vision, both classification errors and time to decision characterize the quality of an algorithmic solution. We show how to formalize such problems in the framework of sequential decisionmaking and derive quasi-optimal time-constrained solutions for three vision problems. The methodology is applied to face and interest point detection and to the RANSAC robust estimator. Error rates of the face detector proposed algorithm are comparable to the state-of-the-art methods. In the interest point application, the output of the Hessian-Laplace detector [9] is approximated by a sequential WaldBoost classifier which is about five times faster than the original with comparable repeatability. A sequential strategy based on Wald’s SPRT for evaluation of model quality in RANSAC leads to significant speed-up in geometric matching problems.eng
dc.language.isocescze
dc.publisherIEEEcze
dc.rights© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.eng
dc.titleWald’s Sequential Analysis for Time-constrained Vision Problemscze
dc.typepříspěvek z konference - elektronickýcze


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