Are younger people more difficult to identify or just a peer-to-peer effect

Wai Han Ho*, Paul Watters, Dominic Verity

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

Recent investigations into the effect of age on face identification concluded that it was more difficult to identify younger people than older ones. The identification rates of the different age groups were, however, not measured under identical conditions. There was a significantly higher percentage of younger people in all the face image samples. We found that a person from any age group will find that they look more similar to another person from the same age group, as opposed to someone from another age group. The experiments we carried out using samples that have an evenly distributed age range did not show a statistically significant difference between the sample age groups.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings
EditorsWalter G. Kropsatsch, Martin Kampel, Allan Hanbury
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Pages351-359
Number of pages9
Volume4673 LNCS
ISBN (Print)9783540742715
DOIs
Publication statusPublished - 2007
Event12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007 - Vienna, Austria
Duration: 27 Aug 200729 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4673 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
CountryAustria
CityVienna
Period27/08/0729/08/07

Keywords

  • aging
  • face
  • identification
  • biometrics

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  • Cite this

    Ho, W. H., Watters, P., & Verity, D. (2007). Are younger people more difficult to identify or just a peer-to-peer effect. In W. G. Kropsatsch, M. Kampel, & A. Hanbury (Eds.), Computer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings (Vol. 4673 LNCS, pp. 351-359). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4673 LNCS). Berlin; Heidelberg: Springer, Springer Nature. https://doi.org/10.1007/978-3-540-74272-2_44