The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2017.080660
PDF

Facial Expression Recognition using Hybrid Texture Features based Ensemble Classifier

Author 1: M. Arfan Jaffar

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 6, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Communication is fundamental to humans. In the literature, it has been shown through many scientific research studies that human communication ranges from 54 to 94 percent is non-verbal. Facial expressions are the most of the important part of the non-verbal communication and it is the most promising way for people to communicate their feelings and emotions to represent their intentions. Pervasive computing and ambient intelligence is required to develop human-centered systems that actively react to complex human communication happening naturally. Therefore, Facial Expression Recognition (FER) system is required that can be used for such type of problem. In this paper, FER system has been proposed by using hybrid texture features to predict the expressions of human. Existing FER system has a problem that these systems show discrepancies in different cultures and ethnicities. Proposed systems also solve this type of problem by using hybrid texture features which are invariant to scale as well as rotate. For texture features, Gabor LBP (GLBP) features have been used to classify expressions by using Random Forest Classifier. Experimentation has been performed on different facial databases that demonstrate promising results.

Keywords: Expression classification; ensemble; adaboost; facial; features

M. Arfan Jaffar, “Facial Expression Recognition using Hybrid Texture Features based Ensemble Classifier” International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080660

@article{Jaffar2017,
title = {Facial Expression Recognition using Hybrid Texture Features based Ensemble Classifier},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080660},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080660},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {6},
author = {M. Arfan Jaffar}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org