Facial expression recognition using extended local binary patterns of 3D curvature

Soon Yong Chun; Chan Su Lee; Sang Heon Lee

doi:10.1007/978-94-007-6738-6_124

Facial expression recognition using extended local binary patterns of 3D curvature

Soon Yong Chun
, Chan Su Lee
, Sang Heon Lee

Division of Automotive Technology

Yeungnam University

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

10 Scopus citations

Abstract

This paper presents extended local binary patterns (LBP) for facial expression analysis from 3D depth map images. Recognition of facial expressions is important to understand human emotion and develop affective human computer interaction. LBP and its extensions are frequently used for texture classification and face identification and detection. In the 3D surface analysis, curvature is very important characteristics. This paper presents an extension of LBP for modeling curvature from 3D depth map images. The extended curvature LBP (CLBP) is used for facial expression recognition. Experimental results using Bosphorus facial expression database show better performance by 3D curvature and the combination of 3D curvature and 2D images than by conventional 2D or 2D + 3D approaches.

Original language	English
Title of host publication	Multimedia and Ubiquitous Engineering, MUE 2013
Pages	1005-1012
Number of pages	8
DOIs	https://doi.org/10.1007/978-94-007-6738-6_124
State	Published - 2013
Event	FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013 - Seoul, Korea, Republic of Duration: 9 May 2013 → 11 May 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	240 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013
Country/Territory	Korea, Republic of
City	Seoul
Period	9/05/13 → 11/05/13

Bibliographical note

Funding Information:
This work was supported by the DGIST R&D Program of the Ministry of Education, Science and Technology of Korea (13-IT-03).

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10.1007/978-94-007-6738-6_124

Cite this

@inproceedings{1d88ce8fd8ee49ac8f043c9058b8bf53,

title = "Facial expression recognition using extended local binary patterns of 3D curvature",

abstract = "This paper presents extended local binary patterns (LBP) for facial expression analysis from 3D depth map images. Recognition of facial expressions is important to understand human emotion and develop affective human computer interaction. LBP and its extensions are frequently used for texture classification and face identification and detection. In the 3D surface analysis, curvature is very important characteristics. This paper presents an extension of LBP for modeling curvature from 3D depth map images. The extended curvature LBP (CLBP) is used for facial expression recognition. Experimental results using Bosphorus facial expression database show better performance by 3D curvature and the combination of 3D curvature and 2D images than by conventional 2D or 2D + 3D approaches.",

author = "Chun, \{Soon Yong\} and Lee, \{Chan Su\} and Lee, \{Sang Heon\}",

note = "Funding Information: This work was supported by the DGIST R\&D Program of the Ministry of Education, Science and Technology of Korea (13-IT-03).; FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013 ; Conference date: 09-05-2013 Through 11-05-2013",

year = "2013",

doi = "10.1007/978-94-007-6738-6\_124",

language = "English",

isbn = "9789400767379",

series = "Lecture Notes in Electrical Engineering",

pages = "1005--1012",

booktitle = "Multimedia and Ubiquitous Engineering, MUE 2013",

}

Chun, SY, Lee, CS & Lee, SH 2013, Facial expression recognition using extended local binary patterns of 3D curvature. in Multimedia and Ubiquitous Engineering, MUE 2013. Lecture Notes in Electrical Engineering, vol. 240 LNEE, pp. 1005-1012, FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013, Seoul, Korea, Republic of, 9/05/13. https://doi.org/10.1007/978-94-007-6738-6_124

TY - GEN

T1 - Facial expression recognition using extended local binary patterns of 3D curvature

AU - Chun, Soon Yong

AU - Lee, Chan Su

AU - Lee, Sang Heon

N1 - Funding Information: This work was supported by the DGIST R&D Program of the Ministry of Education, Science and Technology of Korea (13-IT-03).

PY - 2013

Y1 - 2013

N2 - This paper presents extended local binary patterns (LBP) for facial expression analysis from 3D depth map images. Recognition of facial expressions is important to understand human emotion and develop affective human computer interaction. LBP and its extensions are frequently used for texture classification and face identification and detection. In the 3D surface analysis, curvature is very important characteristics. This paper presents an extension of LBP for modeling curvature from 3D depth map images. The extended curvature LBP (CLBP) is used for facial expression recognition. Experimental results using Bosphorus facial expression database show better performance by 3D curvature and the combination of 3D curvature and 2D images than by conventional 2D or 2D + 3D approaches.

AB - This paper presents extended local binary patterns (LBP) for facial expression analysis from 3D depth map images. Recognition of facial expressions is important to understand human emotion and develop affective human computer interaction. LBP and its extensions are frequently used for texture classification and face identification and detection. In the 3D surface analysis, curvature is very important characteristics. This paper presents an extension of LBP for modeling curvature from 3D depth map images. The extended curvature LBP (CLBP) is used for facial expression recognition. Experimental results using Bosphorus facial expression database show better performance by 3D curvature and the combination of 3D curvature and 2D images than by conventional 2D or 2D + 3D approaches.

UR - https://www.scopus.com/pages/publications/84880715951

U2 - 10.1007/978-94-007-6738-6_124

DO - 10.1007/978-94-007-6738-6_124

M3 - Conference contribution

AN - SCOPUS:84880715951

SN - 9789400767379

T3 - Lecture Notes in Electrical Engineering

SP - 1005

EP - 1012

BT - Multimedia and Ubiquitous Engineering, MUE 2013

T2 - FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013

Y2 - 9 May 2013 through 11 May 2013

ER -

Facial expression recognition using extended local binary patterns of 3D curvature

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