Review on the effects of age, gender, and race demographics on automatic face recognition

Salem Hamed Abdurrahim, Salina Abdul Samad, Aqilah Baseri Huddin

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The performance of face recognition algorithms is affected by external factors and internal subject characteristics. Identifying these aspects and understanding their behaviors on performance can aid in predicting the performance of algorithms and in designing suitable acquisition settings at prospective locations to enhance performance. Factors that affect the performance of face recognition systems, such as pose, illumination, expression, and image resolution, are recognized as face recognition problems. These are substantially studied, and many algorithms have been developed to tackle these problems. However, the influence of population demographics (i.e., race, age, and gender) on face recognition performance has not received considerable attention. Early findings that deal with demographic influence give conflicting results. The studies conducted in the last decade resolve some of the contentions. Nonetheless, some findings have not reached consensus. Existing reviews on the influence of covariates are either outdated or do not cover the influence of demographic covariates on the performance of face recognition algorithms. This paper gives an intensive and focused review that covers recent research on demographic covariates. The effects of age, gender, and race covariates on face recognition are summarized based on these findings, and suggestions on the future direction of the field are given to have a significant understanding of these effects individually and their interactions with one another.

Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalVisual Computer
DOIs
Publication statusAccepted/In press - 23 Aug 2017

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Face recognition
gender
performance
Image resolution
Lighting
interaction

Keywords

  • Age
  • Demographic covariates
  • Face recognition
  • Gender
  • Race

ASJC Scopus subject areas

  • Software
  • Education
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

Review on the effects of age, gender, and race demographics on automatic face recognition. / Abdurrahim, Salem Hamed; Abdul Samad, Salina; Huddin, Aqilah Baseri.

In: Visual Computer, 23.08.2017, p. 1-14.

Research output: Contribution to journalArticle

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