Mean-shift based mixture model for face detection in color image

Tze Yin Chow; Kin Man Lam

doi:10.1109/ICIP.2004.1418826

Mean-shift based mixture model for face detection in color image

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

6 Citations (Scopus)

Abstract

Human face detection is a challenging task under different lighting conditions. In this paper, we propose an efficient and reliable algorithm to detect human faces in an image. In our algorithm, skin-colored pixels under various lighting conditions are identified by using a region-based approach. Within the detected skin-color regions, a ratio method is proposed to determine possible eye candidates. Two eye candidates form a possible face region, which is then verified by means of a two-stage procedure with an eigenmask. Experimental results based on the HHI MPEG-7 face database show that this face detection algorithm is efficient and reliable under different lighting conditions.

Original language	English
Title of host publication	2004 International Conference on Image Processing, ICIP 2004
Pages	601-604
Number of pages	4
Volume	1
DOIs	https://doi.org/10.1109/ICIP.2004.1418826
Publication status	Published - 1 Dec 2004
Event	2004 International Conference on Image Processing, ICIP 2004 - , Singapore Duration: 18 Oct 2004 → 21 Oct 2004

Conference

Conference	2004 International Conference on Image Processing, ICIP 2004
Country/Territory	Singapore
Period	18/10/04 → 21/10/04

ASJC Scopus subject areas

Engineering(all)

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10.1109/ICIP.2004.1418826

Cite this

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title = "Mean-shift based mixture model for face detection in color image",

abstract = "Human face detection is a challenging task under different lighting conditions. In this paper, we propose an efficient and reliable algorithm to detect human faces in an image. In our algorithm, skin-colored pixels under various lighting conditions are identified by using a region-based approach. Within the detected skin-color regions, a ratio method is proposed to determine possible eye candidates. Two eye candidates form a possible face region, which is then verified by means of a two-stage procedure with an eigenmask. Experimental results based on the HHI MPEG-7 face database show that this face detection algorithm is efficient and reliable under different lighting conditions.",

author = "Chow, {Tze Yin} and Lam, {Kin Man}",

year = "2004",

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isbn = "0780385543",

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AU - Lam, Kin Man

PY - 2004/12/1

Y1 - 2004/12/1

N2 - Human face detection is a challenging task under different lighting conditions. In this paper, we propose an efficient and reliable algorithm to detect human faces in an image. In our algorithm, skin-colored pixels under various lighting conditions are identified by using a region-based approach. Within the detected skin-color regions, a ratio method is proposed to determine possible eye candidates. Two eye candidates form a possible face region, which is then verified by means of a two-stage procedure with an eigenmask. Experimental results based on the HHI MPEG-7 face database show that this face detection algorithm is efficient and reliable under different lighting conditions.

AB - Human face detection is a challenging task under different lighting conditions. In this paper, we propose an efficient and reliable algorithm to detect human faces in an image. In our algorithm, skin-colored pixels under various lighting conditions are identified by using a region-based approach. Within the detected skin-color regions, a ratio method is proposed to determine possible eye candidates. Two eye candidates form a possible face region, which is then verified by means of a two-stage procedure with an eigenmask. Experimental results based on the HHI MPEG-7 face database show that this face detection algorithm is efficient and reliable under different lighting conditions.

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U2 - 10.1109/ICIP.2004.1418826

DO - 10.1109/ICIP.2004.1418826

M3 - Conference article published in proceeding or book

SN - 0780385543

VL - 1

SP - 601

EP - 604

BT - 2004 International Conference on Image Processing, ICIP 2004

T2 - 2004 International Conference on Image Processing, ICIP 2004

Y2 - 18 October 2004 through 21 October 2004

ER -

Mean-shift based mixture model for face detection in color image

Abstract

Conference

ASJC Scopus subject areas

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