An application of simultaneous perturbation stochastic approximation (SPSA) algorithm with two measurements per iteration to the problem of object tracking on video is discussed. The upper bound of mean square estimation error is determined in case of once differentiable functional and almost arbitrary noises. Weak restrictions on uncertainty allow to use random sampling instead of full pixelwise difference calculation. The experiments show significant increase in performance of object tracking comparing to the classical Lucas-Kanade algorithm. The results can be generalized to improve more recent kernel-based tracking methods.

Original languageEnglish
Title of host publicationNESTER 2009: NETWORKED EMBEDDED AND CONTROL SYSTEM TECHNOLOGIES: EUROPEAN AND RUSSIAN R&D COOPERATION, PROCEEDINGS
EditorsA Pascoal, Ufnarovsky
PublisherInstitute for Systems and Technologies of Information, Control and Communication
Pages66-74
Number of pages9
ISBN (Print)978-989-674-004-7
StatePublished - 2009
Event1st International Workshop on Networked Embedded and Control System Technologies/European and Russian R&D Cooperation Workshop - Milan, Italy
Duration: 4 Jul 20095 Jul 2009

Conference

Conference1st International Workshop on Networked Embedded and Control System Technologies/European and Russian R&D Cooperation Workshop
Country/TerritoryItaly
CityMilan
Period4/07/095/07/09

    Research areas

  • STOCHASTIC-APPROXIMATION, ALGORITHM, PERTURBATION

ID: 4405009