Object tracking in nonuniform illumination using space-variant correlation filters

Víctor Hugo Díaz-Raḿirez, Kenia Picos, Vitaly Kober

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

6 Scopus citations

Abstract

A reliable system for recognition and tracking of a moving target in nonuniformly illuminated scenes is presented. The system employs a filter bank of space-variant correlation filters adapted to local statistical parameters of the observed scene in each frame. When a scene frame is captured, a fragment of interest is constructed in the frame around predicted location of the target based on a kinematic model. The fragment is firstly pointwise processed to correct the illumination. Afterwards, the state of the target is estimated from the restored fragment by employing a bank of space-variant correlation filters. The performance of the proposed system in terms of object recognition and tracking is tested with nonuniformly illuminated and noisy scenes. The results are compared with those of common techniques based on correlation filtering.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 18th Iberoamerican Congress, CIARP 2013, Proceedings
Pages455-462
Number of pages8
EditionPART 2
DOIs
StatePublished - 2013
Event18th Iberoamerican Congress on Pattern Recognition, CIARP 2013 - Havana, Cuba
Duration: 20 Nov 201323 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8259 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th Iberoamerican Congress on Pattern Recognition, CIARP 2013
Country/TerritoryCuba
CityHavana
Period20/11/1323/11/13

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