Localization of human eyes based on a series of binary images

Jiatao Song; Jilin Liu; Zheru Chi; Wei Wang

doi:10.1109/ICME.2004.1394435

Localization of human eyes based on a series of binary images

Jiatao Song, Jilin Liu, Zheru Chi, Wei Wang

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

5 Citations (Scopus)

Abstract

In this paper, a new method for eyes localization is presented. By incorporating some geometrical constraints of eyes, our method includes such procedures as eyes image segmentation, eye candidates selection and eyeball detection. In order to locate the eyes more precisely, the valley map transformed from the grayscale face image using an arithmetical morphology method is successively binarized with a series of threshold values determined adoptively, and many possible eyeball candidates are extracted from them. The final position of the two eyes is obtained using a statistical method. Experimental results on AR and Yale face databases show that a locating rate of over 94% and an average locating disparity of below 2 pixels can be achieved.

Original language	English
Title of host publication	2004 IEEE International Conference on Multimedia and Expo (ICME)
Pages	1199-1202
Number of pages	4
Volume	2
DOIs	https://doi.org/10.1109/ICME.2004.1394435
Publication status	Published - 1 Dec 2004
Event	2004 IEEE International Conference on Multimedia and Expo (ICME) - Taipei, Taiwan Duration: 27 Jun 2004 → 30 Jun 2004

Conference

Conference	2004 IEEE International Conference on Multimedia and Expo (ICME)
Country/Territory	Taiwan
City	Taipei
Period	27/06/04 → 30/06/04

Keywords

Eye
Image segmentation
Image sequences
Object detection
Statistical analysis

ASJC Scopus subject areas

Engineering(all)

More information

10.1109/ICME.2004.1394435

Cite this

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title = "Localization of human eyes based on a series of binary images",

abstract = "In this paper, a new method for eyes localization is presented. By incorporating some geometrical constraints of eyes, our method includes such procedures as eyes image segmentation, eye candidates selection and eyeball detection. In order to locate the eyes more precisely, the valley map transformed from the grayscale face image using an arithmetical morphology method is successively binarized with a series of threshold values determined adoptively, and many possible eyeball candidates are extracted from them. The final position of the two eyes is obtained using a statistical method. Experimental results on AR and Yale face databases show that a locating rate of over 94% and an average locating disparity of below 2 pixels can be achieved.",

keywords = "Eye, Image segmentation, Image sequences, Object detection, Statistical analysis",

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doi = "10.1109/ICME.2004.1394435",

language = "English",

isbn = "0780386035",

volume = "2",

pages = "1199--1202",

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TY - GEN

T1 - Localization of human eyes based on a series of binary images

AU - Song, Jiatao

AU - Liu, Jilin

AU - Chi, Zheru

AU - Wang, Wei

PY - 2004/12/1

Y1 - 2004/12/1

N2 - In this paper, a new method for eyes localization is presented. By incorporating some geometrical constraints of eyes, our method includes such procedures as eyes image segmentation, eye candidates selection and eyeball detection. In order to locate the eyes more precisely, the valley map transformed from the grayscale face image using an arithmetical morphology method is successively binarized with a series of threshold values determined adoptively, and many possible eyeball candidates are extracted from them. The final position of the two eyes is obtained using a statistical method. Experimental results on AR and Yale face databases show that a locating rate of over 94% and an average locating disparity of below 2 pixels can be achieved.

AB - In this paper, a new method for eyes localization is presented. By incorporating some geometrical constraints of eyes, our method includes such procedures as eyes image segmentation, eye candidates selection and eyeball detection. In order to locate the eyes more precisely, the valley map transformed from the grayscale face image using an arithmetical morphology method is successively binarized with a series of threshold values determined adoptively, and many possible eyeball candidates are extracted from them. The final position of the two eyes is obtained using a statistical method. Experimental results on AR and Yale face databases show that a locating rate of over 94% and an average locating disparity of below 2 pixels can be achieved.

KW - Eye

KW - Image segmentation

KW - Image sequences

KW - Object detection

KW - Statistical analysis

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U2 - 10.1109/ICME.2004.1394435

DO - 10.1109/ICME.2004.1394435

M3 - Conference article published in proceeding or book

SN - 0780386035

SN - 9780780386037

VL - 2

SP - 1199

EP - 1202

BT - 2004 IEEE International Conference on Multimedia and Expo (ICME)

T2 - 2004 IEEE International Conference on Multimedia and Expo (ICME)

Y2 - 27 June 2004 through 30 June 2004

ER -

Localization of human eyes based on a series of binary images

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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