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Face Classification using a New Local Texture Descriptor

Published: 17 October 2017 Publication History

Abstract

Face recognition has received significant attention during the past several years. It is a challenge task because faces can be affected by scale, noises, face expression, illumination, color or pose variations. The most robust methodologies related to these variations are based on "key points?" localization, followed by the application of a local descriptor to each surrounding region. Such descriptors are associated to clustering algorithms or histogram representation based on Bag of Features (BoF). In the BoF approach, the codebook can effectively describe objects by their appearance based on local texture. Based on texture descriptors proposed previously for image detection, we propose in this paper the application of such descriptors for face recognition. We evaluate the performance of our methodology using Feret, ORL and Yale databases, comparing our descriptor against SIFT and LIOP descriptors, and also other methodologies recently published in the literature.

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Cited By

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  • (2018)Face Recognition Using Local Mapped Pattern and Genetic AlgorithmsProceedings of the International Conference on Pattern Recognition and Artificial Intelligence10.1145/3243250.3243262(11-17)Online publication date: 15-Aug-2018

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cover image ACM Other conferences
WebMedia '17: Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web
October 2017
522 pages
ISBN:9781450350969
DOI:10.1145/3126858
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • SBC: Brazilian Computer Society
  • CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
  • CGIBR: Comite Gestor da Internet no Brazil
  • CAPES: Brazilian Higher Education Funding Council

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2017

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Author Tags

  1. bag-of-features
  2. face recognition
  3. feret database
  4. svm

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  • Short-paper

Funding Sources

  • FAPESP

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Webmedia '17
Sponsor:
  • SBC
  • CNPq
  • CGIBR
  • CAPES
Webmedia '17: Brazilian Symposium on Multimedia and the Web
October 17 - 20, 2017
RS, Gramado, Brazil

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WebMedia '17 Paper Acceptance Rate 38 of 138 submissions, 28%;
Overall Acceptance Rate 270 of 873 submissions, 31%

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Cited By

View all
  • (2018)Face Recognition Using Local Mapped Pattern and Genetic AlgorithmsProceedings of the International Conference on Pattern Recognition and Artificial Intelligence10.1145/3243250.3243262(11-17)Online publication date: 15-Aug-2018

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