Occluded Image Recognition with Extended Nonnegative Matrix Factorization

Viet Hang Duong, Manh Quan Bui, Jia Ching Wang

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

1 Scopus citations

Abstract

This paper addresses the challenge of recognizing face and facial expression under occlusion situations. We have introduced an extension of nonnegative matrix factorization called angle and graph constrained nonnegative matrix factorization (AGNRIF). The proposed model is developed in term of minimizing angle of basic cone and preserving the geometrical structure of the projective data. The experimental results in the context of occluded images demonstrate that the technique of enforcing constraints on both basic and encoding matrices works well and the AGNMF method shows superior performance to other conventional NRIF approaches.

Original languageEnglish
Title of host publicationNICS 2018 - Proceedings of 2018 5th NAFOSTED Conference on Information and Computer Science
EditorsHo Tu Bao, Le Anh Cuong, Ho Van Khuong, Bui Thu Lam
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages200-204
Number of pages5
ISBN (Electronic)9781538679838
DOIs
StatePublished - 9 Jan 2019
Event5th NAFOSTED Conference on Information and Computer Science, NICS 2018 - Ho Chi Minh City, Viet Nam
Duration: 23 Nov 201824 Nov 2018

Publication series

NameNICS 2018 - Proceedings of 2018 5th NAFOSTED Conference on Information and Computer Science

Conference

Conference5th NAFOSTED Conference on Information and Computer Science, NICS 2018
Country/TerritoryViet Nam
CityHo Chi Minh City
Period23/11/1824/11/18

Keywords

  • Face recognition
  • Facial expression recognition
  • Nonnegative matrix factorization

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