Feature extraction through binary pattern of phase congruency for facial expression recognition

Although facial expression plays an important role in human interaction, automated facial expression analysis is still a challenging task. This paper presents a novel facial descriptor based on Phase Congruency (PC) and Local Binary Pattern (LBP) for facial expression recognition. The proposed descr...

Full description

Saved in:
Bibliographic Details
Main Authors: Shojaeilangari, Seyedehsamaneh, Yau, Wei-Yun, Li, Jun, Teoh, Eam Khwang
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/100615
http://hdl.handle.net/10220/18012
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-100615
record_format dspace
spelling sg-ntu-dr.10356-1006152020-03-07T13:24:50Z Feature extraction through binary pattern of phase congruency for facial expression recognition Shojaeilangari, Seyedehsamaneh Yau, Wei-Yun Li, Jun Teoh, Eam Khwang School of Electrical and Electronic Engineering International Conference on Control Automation Robotics & Vision (12th : 2012 : Guangzhou, China) A*STAR Institute for Infocomm Research DRNTU::Engineering::Electrical and electronic engineering Although facial expression plays an important role in human interaction, automated facial expression analysis is still a challenging task. This paper presents a novel facial descriptor based on Phase Congruency (PC) and Local Binary Pattern (LBP) for facial expression recognition. The proposed descriptor, named Binary Pattern of Phase Congruency (BPPC), is an oriented and multi-scale local descriptor that is able to encode various patterns of face images. It is constructed by applying LBP on the oriented PC images. We evaluated the proposed method using the Cohn-Kanade (CK+) database. In our experiment, we achieved an overall detection rate of 93.83% for the six basic emotions. This shows the effectiveness of the proposed method. ASTAR (Agency for Sci., Tech. and Research, S’pore) Accepted version 2013-12-04T03:44:11Z 2019-12-06T20:25:25Z 2013-12-04T03:44:11Z 2019-12-06T20:25:25Z 2012 2012 Conference Paper Shojaeilangari, S., Yau, W. Y., Li, J., & Teoh, E. K. (2012). Feature extraction through binary pattern of phase congruency for facial expression recognition. 12th International Conference on Control Automation Robotics & Vision (ICARCV), 166-170. https://hdl.handle.net/10356/100615 http://hdl.handle.net/10220/18012 10.1109/ICARCV.2012.6485152 en © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ICARCV.2012.6485152]. 5 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Shojaeilangari, Seyedehsamaneh
Yau, Wei-Yun
Li, Jun
Teoh, Eam Khwang
Feature extraction through binary pattern of phase congruency for facial expression recognition
description Although facial expression plays an important role in human interaction, automated facial expression analysis is still a challenging task. This paper presents a novel facial descriptor based on Phase Congruency (PC) and Local Binary Pattern (LBP) for facial expression recognition. The proposed descriptor, named Binary Pattern of Phase Congruency (BPPC), is an oriented and multi-scale local descriptor that is able to encode various patterns of face images. It is constructed by applying LBP on the oriented PC images. We evaluated the proposed method using the Cohn-Kanade (CK+) database. In our experiment, we achieved an overall detection rate of 93.83% for the six basic emotions. This shows the effectiveness of the proposed method.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Shojaeilangari, Seyedehsamaneh
Yau, Wei-Yun
Li, Jun
Teoh, Eam Khwang
format Conference or Workshop Item
author Shojaeilangari, Seyedehsamaneh
Yau, Wei-Yun
Li, Jun
Teoh, Eam Khwang
author_sort Shojaeilangari, Seyedehsamaneh
title Feature extraction through binary pattern of phase congruency for facial expression recognition
title_short Feature extraction through binary pattern of phase congruency for facial expression recognition
title_full Feature extraction through binary pattern of phase congruency for facial expression recognition
title_fullStr Feature extraction through binary pattern of phase congruency for facial expression recognition
title_full_unstemmed Feature extraction through binary pattern of phase congruency for facial expression recognition
title_sort feature extraction through binary pattern of phase congruency for facial expression recognition
publishDate 2013
url https://hdl.handle.net/10356/100615
http://hdl.handle.net/10220/18012
_version_ 1681049580337102848