Automatic Eye Detection Error as a Predictor of Face Recognition Performance

Abhishek Dutta; Raymond Veldhuis; Luuk Spreeuwers

Automatic Eye Detection Error as a Predictor of Face Recognition Performance

Abhishek Dutta, Raymond Veldhuis, Luuk Spreeuwers

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

16 Citations (Scopus)

59 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 language	English
Title of host publication	35rd 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 publication	Eindhoven, The Netherlands, May 12-13, 2014
Place of Publication	Eindhoven
Publisher	Werkgemeenschap voor Informatie- en Communicatietheorie (WIC)
Pages	89-96
Number of pages	8
ISBN (Print)	978-90-365-3383-6
Publication status	Published - May 2014
Event	35th WIC Symposium on Information Theory in the Benelux 2014 - Eindhoven, Netherlands Duration: 12 May 2014 → 13 May 2014 Conference number: 35

Conference

Conference	35th WIC Symposium on Information Theory in the Benelux 2014
Country/Territory	Netherlands
City	Eindhoven
Period	12/05/14 → 13/05/14

Keywords

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

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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). 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 = may,

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",

note = "35th WIC Symposium on Information Theory in the Benelux 2014 ; Conference date: 12-05-2014 Through 13-05-2014",

}

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 proceeding › Conference contribution › Academic › peer-review

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AU - Spreeuwers, Luuk

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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

T2 - 35th WIC Symposium on Information Theory in the Benelux 2014

Y2 - 12 May 2014 through 13 May 2014

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

Automatic Eye Detection Error as a Predictor of Face Recognition Performance

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