Automatic Eye Detection Error as a Predictor of Face Recognition Performance

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

11 Citations (Scopus)
10 Downloads (Pure)

Abstract

Various facial image quality parameters like pose, illumination, noise, resolution, etc are known to be a predictor of face recognition performance. However, there still remain many other properties of facial images that are not captured by the existing quality parameters. In this paper, we propose a novel image quality parameter called the Automatic Eye Detection Error (AEDE) which measures the difference between manually located and automatically detected eye coordinates. Our experiment results carried out using FaceVACS recognition system and the MultiPIE dataset show that AEDE is indeed a predictor of face recognition performance.
Original languageEnglish
Title of host publication35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux
Subtitle of host publicationEindhoven, The Netherlands, May 12-13, 2014
Place of PublicationEindhoven
PublisherWerkgemeenschap voor Informatie- en Communicatietheorie (WIC)
Pages89-96
Number of pages8
ISBN (Print)978-90-365-3383-6
Publication statusPublished - May 2014
Event35th WIC Symposium on Information Theory in the Benelux 2014 - Eindhoven, Netherlands
Duration: 12 May 201413 May 2014
Conference number: 35

Conference

Conference35th WIC Symposium on Information Theory in the Benelux 2014
CountryNetherlands
CityEindhoven
Period12/05/1413/05/14

Fingerprint

Error detection
Face recognition
Image quality
Lighting
Experiments

Keywords

  • SCS-Safety
  • Performance Prediction
  • EWI-24813
  • IR-91485
  • Face Recognition
  • METIS-305908
  • Eye Detection Error

Cite this

Dutta, A., Veldhuis, R., & Spreeuwers, L. (2014). Automatic Eye Detection Error as a Predictor of Face Recognition Performance. In 35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux: Eindhoven, The Netherlands, May 12-13, 2014 (pp. 89-96). Eindhoven: Werkgemeenschap voor Informatie- en Communicatietheorie (WIC).
Dutta, Abhishek ; Veldhuis, Raymond ; Spreeuwers, Luuk. / Automatic Eye Detection Error as a Predictor of Face Recognition Performance. 35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux: Eindhoven, The Netherlands, May 12-13, 2014. Eindhoven : Werkgemeenschap voor Informatie- en Communicatietheorie (WIC), 2014. pp. 89-96
@inproceedings{ea3e08f348144fe1a083759ff65a53ef,
title = "Automatic Eye Detection Error as a Predictor of Face Recognition Performance",
abstract = "Various facial image quality parameters like pose, illumination, noise, resolution, etc are known to be a predictor of face recognition performance. However, there still remain many other properties of facial images that are not captured by the existing quality parameters. In this paper, we propose a novel image quality parameter called the Automatic Eye Detection Error (AEDE) which measures the difference between manually located and automatically detected eye coordinates. Our experiment results carried out using FaceVACS recognition system and the MultiPIE dataset show that AEDE is indeed a predictor of face recognition performance.",
keywords = "SCS-Safety, Performance Prediction, EWI-24813, IR-91485, Face Recognition, METIS-305908, Eye Detection Error",
author = "Abhishek Dutta and Raymond Veldhuis and Luuk Spreeuwers",
year = "2014",
month = "5",
language = "English",
isbn = "978-90-365-3383-6",
pages = "89--96",
booktitle = "35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux",
publisher = "Werkgemeenschap voor Informatie- en Communicatietheorie (WIC)",
address = "Netherlands",

}

Dutta, A, Veldhuis, R & Spreeuwers, L 2014, Automatic Eye Detection Error as a Predictor of Face Recognition Performance. in 35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux: Eindhoven, The Netherlands, May 12-13, 2014. Werkgemeenschap voor Informatie- en Communicatietheorie (WIC), Eindhoven, pp. 89-96, 35th WIC Symposium on Information Theory in the Benelux 2014, Eindhoven, Netherlands, 12/05/14.

Automatic Eye Detection Error as a Predictor of Face Recognition Performance. / Dutta, Abhishek; Veldhuis, Raymond; Spreeuwers, Luuk.

35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux: Eindhoven, The Netherlands, May 12-13, 2014. Eindhoven : Werkgemeenschap voor Informatie- en Communicatietheorie (WIC), 2014. p. 89-96.

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

TY - GEN

T1 - Automatic Eye Detection Error as a Predictor of Face Recognition Performance

AU - Dutta, Abhishek

AU - Veldhuis, Raymond

AU - Spreeuwers, Luuk

PY - 2014/5

Y1 - 2014/5

N2 - Various facial image quality parameters like pose, illumination, noise, resolution, etc are known to be a predictor of face recognition performance. However, there still remain many other properties of facial images that are not captured by the existing quality parameters. In this paper, we propose a novel image quality parameter called the Automatic Eye Detection Error (AEDE) which measures the difference between manually located and automatically detected eye coordinates. Our experiment results carried out using FaceVACS recognition system and the MultiPIE dataset show that AEDE is indeed a predictor of face recognition performance.

AB - Various facial image quality parameters like pose, illumination, noise, resolution, etc are known to be a predictor of face recognition performance. However, there still remain many other properties of facial images that are not captured by the existing quality parameters. In this paper, we propose a novel image quality parameter called the Automatic Eye Detection Error (AEDE) which measures the difference between manually located and automatically detected eye coordinates. Our experiment results carried out using FaceVACS recognition system and the MultiPIE dataset show that AEDE is indeed a predictor of face recognition performance.

KW - SCS-Safety

KW - Performance Prediction

KW - EWI-24813

KW - IR-91485

KW - Face Recognition

KW - METIS-305908

KW - Eye Detection Error

M3 - Conference contribution

SN - 978-90-365-3383-6

SP - 89

EP - 96

BT - 35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux

PB - Werkgemeenschap voor Informatie- en Communicatietheorie (WIC)

CY - Eindhoven

ER -

Dutta A, Veldhuis R, Spreeuwers L. Automatic Eye Detection Error as a Predictor of Face Recognition Performance. In 35rd WIC Symposium on Information Theory in the Benelux and The 4th WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux: Eindhoven, The Netherlands, May 12-13, 2014. Eindhoven: Werkgemeenschap voor Informatie- en Communicatietheorie (WIC). 2014. p. 89-96