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Unsupervised Facial Biometric Data Filtering for Age and Gender Estimation
Faculty of Electrical Engineering and Computing, University of Zagreb,.ORCID iD: 0000-0002-5861-7076
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6763-5487
Faculty of Electrical Engineering and Computing, University of Zagreb.
2019 (English)In: Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019), SciTePress, 2019, Vol. 5, p. 209-217Conference paper, Published paper (Refereed)
Abstract [en]

Availability of large training datasets was essential for the recent advancement and success of deep learning methods. Due to the difficulties related to biometric data collection, datasets with age and gender annotations are scarce and usually limited in terms of size and sample diversity. Web-scraping approaches for automatic data collection can produce large amounts weakly labeled noisy data. The unsupervised facial biometric data filtering method presented in this paper greatly reduces label noise levels in web-scraped facial biometric data. Experiments on two large state-of-the-art web-scraped facial datasets demonstrate the effectiveness of the proposed method, with respect to training and validation scores, training convergence, and generalization capabilities of trained age and gender estimators.

Place, publisher, year, edition, pages
SciTePress, 2019. Vol. 5, p. 209-217
Keywords [en]
Biometric, Web-Scraping, Age, Gender
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-154867ISBN: 978-989-758-354-4 (electronic)OAI: oai:DiVA.org:liu-154867DiVA, id: diva2:1292960
Conference
International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Available from: 2019-03-01 Created: 2019-03-01 Last updated: 2019-04-03

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Ahlberg, Jörgen

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf