GI LogoGI Logo
  • Login
Digital Library
    • All of DSpace

      • Communities & Collections
      • Titles
      • Authors
      • By Issue Date
      • Subjects
    • This Collection

      • Titles
      • Authors
      • By Issue Date
      • Subjects
Digital Library Gesellschaft für Informatik e.V.
GI-DL
    • English
    • Deutsch
  • English 
    • English
    • Deutsch
View Item 
  •   DSpace Home
  • Lecture Notes in Informatics
  • Proceedings
  • BIOSIG - Biometrics and Electronic Signatures
  • P282 - BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
  •   DSpace Home
  • Lecture Notes in Informatics
  • Proceedings
  • BIOSIG - Biometrics and Electronic Signatures
  • P282 - BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group
  • View Item

Shallow CNNs for the Reliable Detection of Facial Marks

Author:
Zeinstra, Chris [DBLP] ;
Haasnoot, Erwin [DBLP]
Abstract
Facial marks are local irregularities of skin texture. Their type and/or spatial pattern can be used as a (soft) biometric modality in several applications. A key requirement for a biometric system that utilises facial marks is their reliable detection. Detection methods typically use a blob detector followed by heuristic post processing steps to reduce the number of false positives. In this paper, we consider shallow Convolutional Neural Networks (CNNs) for facial mark detection. The choice of this network type seems natural as it learns multiple (non) blob detectors; shallow refers to the fact that we only consider CNNs up to three layers.We show that (a) these CNNs successfully address the false positive problem, (b) remove the need for post processing steps, and (c) outperform a classic blob detector, approaches taken in previous studies and some other non CNN type classifiers in terms of EER and FMR at TMR=0.95.
  • Citation
  • BibTeX
Zeinstra, C. & Haasnoot, E., (2018). Shallow CNNs for the Reliable Detection of Facial Marks. In: Brömme, A., Busch, C., Dantcheva, A., Rathgeb, C. & Uhl, A. (Hrsg.), BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group. Bonn: Köllen Druck+Verlag GmbH.
@inproceedings{mci/Zeinstra2018,
author = {Zeinstra, Chris AND Haasnoot, Erwin},
title = {Shallow CNNs for the Reliable Detection of Facial Marks},
booktitle = {BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group},
year = {2018},
editor = {Brömme, Arslan AND Busch, Christoph AND Dantcheva, Antitza AND Rathgeb, Christian AND Uhl, Andreas},
publisher = {Köllen Druck+Verlag GmbH},
address = {Bonn}
}
DateienGroesseFormatAnzeige
BIOSIG_2018_paper_16.pdf398.0Kb PDF View/Open

Haben Sie fehlerhafte Angaben entdeckt? Sagen Sie uns Bescheid: Send Feedback

More Info

ISBN: 978-3-88579-676-4
ISSN: 1617-5468
xmlui.MetaDataDisplay.field.date: 2018
Language: en (en)
Content Type: Text/Conference Paper

Keywords

  • Facial Marks
  • Image Processing
  • Forensics
  • CNN.
Collections
  • P282 - BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group [32]

Show full item record


About uns | FAQ | Help | Imprint | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.

 

 


About uns | FAQ | Help | Imprint | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.