Localization and extraction on the eyes, nose and mouth of human face

Shuliang Wang; Xiao Feng; Hehua Chi; Xiuling Wang

doi:10.1109/GRC.2009.5255056

Localization and extraction on the eyes, nose and mouth of human face

Shuliang Wang^*
, Xiao Feng
, Hehua Chi
, Xiuling Wang

^*Corresponding author for this work

Wuhan University

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

3 Citations (Scopus)

Abstract

The traditional gray projection function was mainly utilized in eye localization. In this paper, an optimized function is proposed to simultaneously localize eyes, nose and mouth. This improvement is implemented through three steps. Firstly, by calculating the derivation of the gray projection curve, the stationary points region of eyes (nose or mouth) can be obtained. Secondly, determine the boundaries of those stationary points regions by setting appropriate thresholds. Thirdly, extract facial features, such as eyes, nose, and mouth from the original images in accordance with those boundaries of the respective stationary points region.

Original language	English
Title of host publication	2009 IEEE International Conference on Granular Computing, GRC 2009
Pages	561-564
Number of pages	4
DOIs	https://doi.org/10.1109/GRC.2009.5255056
Publication status	Published - 2009
Externally published	Yes
Event	2009 IEEE International Conference on Granular Computing, GRC 2009 - Nanchang, China Duration: 17 Aug 2009 → 19 Aug 2009

Publication series

Name	2009 IEEE International Conference on Granular Computing, GRC 2009

Conference

Conference	2009 IEEE International Conference on Granular Computing, GRC 2009
Country/Territory	China
City	Nanchang
Period	17/08/09 → 19/08/09

Access to Document

10.1109/GRC.2009.5255056

Cite this

@inproceedings{0b8c4bd0ae004f9e89f5c0ddf1561ad3,

title = "Localization and extraction on the eyes, nose and mouth of human face",

abstract = "The traditional gray projection function was mainly utilized in eye localization. In this paper, an optimized function is proposed to simultaneously localize eyes, nose and mouth. This improvement is implemented through three steps. Firstly, by calculating the derivation of the gray projection curve, the stationary points region of eyes (nose or mouth) can be obtained. Secondly, determine the boundaries of those stationary points regions by setting appropriate thresholds. Thirdly, extract facial features, such as eyes, nose, and mouth from the original images in accordance with those boundaries of the respective stationary points region.",

author = "Shuliang Wang and Xiao Feng and Hehua Chi and Xiuling Wang",

year = "2009",

doi = "10.1109/GRC.2009.5255056",

language = "English",

isbn = "9781424448319",

series = "2009 IEEE International Conference on Granular Computing, GRC 2009",

pages = "561--564",

booktitle = "2009 IEEE International Conference on Granular Computing, GRC 2009",

note = "2009 IEEE International Conference on Granular Computing, GRC 2009 ; Conference date: 17-08-2009 Through 19-08-2009",

}

Wang, S, Feng, X, Chi, H & Wang, X 2009, Localization and extraction on the eyes, nose and mouth of human face. in 2009 IEEE International Conference on Granular Computing, GRC 2009., 5255056, 2009 IEEE International Conference on Granular Computing, GRC 2009, pp. 561-564, 2009 IEEE International Conference on Granular Computing, GRC 2009, Nanchang, China, 17/08/09. https://doi.org/10.1109/GRC.2009.5255056

Localization and extraction on the eyes, nose and mouth of human face. / Wang, Shuliang; Feng, Xiao; Chi, Hehua et al.
2009 IEEE International Conference on Granular Computing, GRC 2009. 2009. p. 561-564 5255056 (2009 IEEE International Conference on Granular Computing, GRC 2009).

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

TY - GEN

T1 - Localization and extraction on the eyes, nose and mouth of human face

AU - Wang, Shuliang

AU - Feng, Xiao

AU - Chi, Hehua

AU - Wang, Xiuling

PY - 2009

Y1 - 2009

N2 - The traditional gray projection function was mainly utilized in eye localization. In this paper, an optimized function is proposed to simultaneously localize eyes, nose and mouth. This improvement is implemented through three steps. Firstly, by calculating the derivation of the gray projection curve, the stationary points region of eyes (nose or mouth) can be obtained. Secondly, determine the boundaries of those stationary points regions by setting appropriate thresholds. Thirdly, extract facial features, such as eyes, nose, and mouth from the original images in accordance with those boundaries of the respective stationary points region.

AB - The traditional gray projection function was mainly utilized in eye localization. In this paper, an optimized function is proposed to simultaneously localize eyes, nose and mouth. This improvement is implemented through three steps. Firstly, by calculating the derivation of the gray projection curve, the stationary points region of eyes (nose or mouth) can be obtained. Secondly, determine the boundaries of those stationary points regions by setting appropriate thresholds. Thirdly, extract facial features, such as eyes, nose, and mouth from the original images in accordance with those boundaries of the respective stationary points region.

UR - https://www.scopus.com/pages/publications/70449886706

U2 - 10.1109/GRC.2009.5255056

DO - 10.1109/GRC.2009.5255056

M3 - Conference contribution

AN - SCOPUS:70449886706

SN - 9781424448319

T3 - 2009 IEEE International Conference on Granular Computing, GRC 2009

SP - 561

EP - 564

BT - 2009 IEEE International Conference on Granular Computing, GRC 2009

T2 - 2009 IEEE International Conference on Granular Computing, GRC 2009

Y2 - 17 August 2009 through 19 August 2009

ER -

Localization and extraction on the eyes, nose and mouth of human face

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this