The Effect of Own-Race Bias (ORB) on Face Recognition

The term "own-race bias" (ORB) describes the situation in which people are more adept at identifying the faces of members of their own race than those of other races. The impact of racial disparities on face recognition accuracy and speed is investigated in this study. Empirical studies have demonstrated the involvement of variables including affect and mental abilities in ORB. While split attention tends to enhance ORB, positive emotions can decrease it. Positive emotional states may also boost cognitive flexibility, which would improve the ability to recognise faces of different races. Research looking at racial disparities in facial features also show quantifiable differences across racial groups. While some studies employ deep learning algorithms to categorise race using face traits, others use anthropometric measurements to identify these differences. Notwithstanding these discoveries, additional research employing more varied samples and longer study durations is necessary due to limitations including biassed data and a disregard for the environment.

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Publication Details

Journal
Journal of Education Humanities and Social Sciences
Published
2024-12-26
DOI
https://doi.org/10.54097/kxk18g29
Primary Topic
Face recognition and analysis
Type
article
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article

The Effect of Own-Race Bias (ORB) on Face Recognition

Junhao Wang
Journal of Education Humanities and Social Sciences
Face recognition and analysis
article

The Effect of Own-Race Bias (ORB) on Face Recognition

Junhao Wang
article en

Abstract

The term "own-race bias" (ORB) describes the situation in which people are more adept at identifying the faces of members of their own race than those of other races. The impact of racial disparities on face recognition accuracy and speed is investigated in this study. Empirical studies have demonstrated the involvement of variables including affect and mental abilities in ORB. While split attention tends to enhance ORB, positive emotions can decrease it. Positive emotional states may also boost cognitive flexibility, which would improve the ability to recognise faces of different races. Research looking at racial disparities in facial features also show quantifiable differences across racial groups. While some studies employ deep learning algorithms to categorise race using face traits, others use anthropometric measurements to identify these differences. Notwithstanding these discoveries, additional research employing more varied samples and longer study durations is necessary due to limitations including biassed data and a disregard for the environment.

Journal of Education Humanities and Social SciencesVol. 45
Chengdu University (CN)
Reduced inequalities
Openalex Percentile: Top 76%
Face recognition and analysis
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