An Improved Face Recognition Algorithm Based on Sparse Representation

Cemil Turan, Shirali Kadyrov, Diana Burissova

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper considers a variation of Sparse Representation-based Classification algorithm. Accuracy and time of evaluation of face recognition are two key performance indicators. This work compares performance of modified Sparse Representation-based Classification algorithm against original Sparse Representation-based Classification algorithm. Yale Face Database B is used to carry MATLAB simulations and results show that modified Sparse Representation-based Classification algorithm outperforms in terms of time. Moreover, the authors study and compare these algorithms when there is only a few training samples per subject is available.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Computing and Network Communications, CoCoNet 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-35
Number of pages4
ISBN (Electronic)9781538659281
DOIs
Publication statusPublished - Sep 28 2018
Event2nd International Conference on Computing and Network Communications, CoCoNet 2018 - Astana, Kazakhstan
Duration: Aug 15 2018Aug 17 2018

Conference

Conference2nd International Conference on Computing and Network Communications, CoCoNet 2018
CountryKazakhstan
CityAstana
Period8/15/188/17/18

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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