Real-time object tracking with correlation filtering and state prediction

Viridiana Contreras, Victor H. Diaz-Ramirez, Vitaly Kober, Juan J. Tapia-Armenta

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A real-time tracking system based on adaptive correlation filtering and state prediction is proposed. The system is able to estimate at high-rate the position of multiple targets within the observed scene by taking into account information of past and present scene-frames. The position of the targets in the current frame is estimated with the help of a bank of composite correlation filters applied to several small regions taken from the observed scene. These small regions are updated in each frame according to information from a state predictor based on the motion model of targets in a twodimensional plane. The proposed system is implemented on a graphics processing unit to take advantage of massive parallelism. Computer simulation results obtained with the proposed system are presented and discussed in terms of tracking accuracy and real-time operation efficiency.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XXXVI
DOIs
StatePublished - 2013
EventApplications of Digital Image Processing XXXVI - San Diego, CA, United States
Duration: 26 Aug 201329 Aug 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8856
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceApplications of Digital Image Processing XXXVI
Country/TerritoryUnited States
CitySan Diego, CA
Period26/08/1329/08/13

Keywords

  • Multiclass object recognition
  • dynamic models
  • graphics processing unit
  • object tracking
  • real-time image processing

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