Towards automated caricature recognition

Brendan F. Klare*, Serhat S. Bucak, Anil K. Jain, Tayfun Akgul

*Corresponding author for this work

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

46 Citations (Scopus)

Abstract

This paper addresses the problem of identifying a subject from a caricature. A caricature is a facial sketch of a subject's face that exaggerates identifiable facial features beyond realism, while still conveying his identity. To enable this task, we propose a set of qualitative facial features that encodes the appearance of both caricatures and photographs. We utilized crowdsourcing, through Amazon's Mechanical Turk service, to assist in the labeling of the qualitative features. Using these features, we combine logistic regression, multiple kernel learning, and support vector machines to generate a similarity score between a caricature and a facial photograph. Experiments are conducted on a dataset of 196 pairs of caricatures and photographs, which we have made publicly available. Through the development of novel feature representations and matching algorithms, this research seeks to help leverage the ability of humans to recognize caricatures to improve automatic face recognition methods.

Original languageEnglish
Title of host publicationProceedings - 2012 5th IAPR International Conference on Biometrics, ICB 2012
Pages139-146
Number of pages8
DOIs
Publication statusPublished - 2012
Event2012 5th IAPR International Conference on Biometrics, ICB 2012 - New Delhi, India
Duration: 29 Mar 20121 Apr 2012

Publication series

NameProceedings - 2012 5th IAPR International Conference on Biometrics, ICB 2012

Conference

Conference2012 5th IAPR International Conference on Biometrics, ICB 2012
Country/TerritoryIndia
CityNew Delhi
Period29/03/121/04/12

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