Robust face tracking with locally-adaptive correlation filtering

Leopoldo N. Gaxiola, Víctor Hugo Díaz-Ramírez, Juan J. Tapia, Arnoldo Diaz-Ramirez, Vitaly Kober

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

11 Scopus citations

Abstract

A face tracking algorithm based on locally-adaptive correlation filtering is proposed. The algorithm is capable to track a face with invariance to pose, gesticulations, occlusions and clutter. The target face is chosen at the beginning of the algorithm. Afterwards, a composite filter is designed to recognize the face in posterior frames. The filter is adapted online using information of current and past scene frames. The adaptive filter is constructed by combining several optimal templates designed for distortion invariant target recognition. Results obtained with the proposed algorithm using real-life scenes, are presented and compared with those obtained with a recent state-of-the-art tracking method, in terms of detection efficiency, tracking accuracy, and speed of processing.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
EditorsEduardo Bayro-Corrochano, Edwin Hancock
PublisherSpringer Verlag
Pages925-932
Number of pages8
ISBN (Electronic)9783319125671
DOIs
StatePublished - 2014
Event19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 - Puerto Vallarta, Mexico
Duration: 2 Nov 20145 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8827
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
Country/TerritoryMexico
CityPuerto Vallarta
Period2/11/145/11/14

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