Accelerated People Tracking using Texture in a Camera Network

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an approach to tracking multiple human subjects within a camera network. A particle filter frame-work is used in which we combine foreground-background subtraction with a novel approach to texture learning and likelihood computation based on an ellipsoid model. As there are inevitable problems with multiple subjects due to occlusion and crossing, we include a robust method to suppress distraction between subjects. To achieve real-time performance, we have also developed our code on a graphics processing unit to achieve a 10-fold reduction in processing time with an approximate frame rate of 10 frames per second.
Original languageEnglish
Title of host publication Proceedings of the International Conference on Computer Vision Theory and Applications 2012
Pages225-234
DOIs
Publication statusPublished - Feb 2012
EventInternational Conference on Computer Vision Theory and Applications 2012 - Rome, Italy
Duration: 24 Feb 201226 Feb 2012

Conference

ConferenceInternational Conference on Computer Vision Theory and Applications 2012
Abbreviated titleVISAPP 2012
CountryItaly
CityRome
Period24/02/1226/02/12

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