Human expression recognition using facial shape based Fourier descriptors fusion

Ali Raza Shahid, Shehryar Khan, Hong Yan

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

3 Citations (Scopus)

Abstract

Dynamic facial expression recognition has many useful applications in social networks, multimedia content analysis, security systems and others. This challenging process must be done under recurrent problems of image illumination and low resolution which changes at partial occlusions. This paper aims to produce a new facial expression recognition method based on the changes in the facial muscles. The geometric features are used to specify the facial regions i.e., mouth, eyes, and nose. The generic Fourier shape descriptor in conjunction with elliptic Fourier shape descriptor is used as an attribute to represent different emotions under frequency spectrum features. Afterwards a multi-class support vector machine is applied for classification of seven human expression. The statistical analysis showed our approach obtained overall competent recognition using 5-fold cross validation with high accuracy on well-known facial expression dataset.

Original languageEnglish
Title of host publication12th International Conference on Machine Vision, ICMV 2019
EditorsWolfgang Osten, Dmitry Nikolaev, Jianhong Zhou
PublisherSPIE
ISBN (Electronic)9781510636439
DOIs
Publication statusPublished - 2020
Event12th International Conference on Machine Vision, ICMV 2019 - Amsterdam, Netherlands
Duration: 16 Nov 201918 Nov 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11433
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference12th International Conference on Machine Vision, ICMV 2019
Country/TerritoryNetherlands
CityAmsterdam
Period16/11/1918/11/19

Keywords

  • Elliptic Fourier shape descriptor
  • Facial expression recognition
  • Generic Fourier shape descriptor

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