A novel phase congruency based descriptor for dynamic facial expression analysis

Representation and classification of dynamic visual events in videos have been an active field of research. This work proposed a novel spatio-temporal descriptor based on phase congruency concept and applied it to recognize facial expression from video sequences. The proposed descriptor comprises hi...

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Main Authors: Shojaeilangari, Seyedehsamaneh, Yau, Wei-Yun, Teoh, Eam Khwang
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2016
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Online Access:https://hdl.handle.net/10356/81599
http://hdl.handle.net/10220/39591
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-815992020-03-07T13:57:25Z A novel phase congruency based descriptor for dynamic facial expression analysis Shojaeilangari, Seyedehsamaneh Yau, Wei-Yun Teoh, Eam Khwang School of Electrical and Electronic Engineering Phase congruency; Spatio-temporal descriptor; Emotion recognition; Facial expression Representation and classification of dynamic visual events in videos have been an active field of research. This work proposed a novel spatio-temporal descriptor based on phase congruency concept and applied it to recognize facial expression from video sequences. The proposed descriptor comprises histograms of dominant phase congruency over multiple 3D orientations to describe both spatial and temporal information of a dynamic event. The advantages of our proposed approach are local and dynamic processing, high accuracy, robustness to image scale variation, and illumination changes. We validated the performance of our proposed approach using the Cohn-Kanade (CK+) database where we achieved 95.44% accuracy in detecting six basic emotions. The approach was also shown to increase classification rates over the baseline results for the AVEC 2011 video subchallenge in detecting four emotion dimensions. We also validated its robustness to illumination and scale variation using our own collected dataset. ASTAR (Agency for Sci., Tech. and Research, S’pore) Accepted version 2016-01-06T06:18:37Z 2019-12-06T14:34:41Z 2016-01-06T06:18:37Z 2019-12-06T14:34:41Z 2014 Journal Article Shojaeilangari, S., Yau, W.-Y., & Teoh, E. K. (2014). A novel phase congruency based descriptor for dynamic facial expression analysis. Pattern Recognition Letters, 49, 55-61. 0167-8655 https://hdl.handle.net/10356/81599 http://hdl.handle.net/10220/39591 10.1016/j.patrec.2014.06.009 en Pattern Recognition Letters © 2014 Elsevier B.V. This is the author created version of a work that has been peer reviewed and accepted for publication by Pattern Recognition Letters, Elsevier B.V. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.patrec.2014.06.009]. 20 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Phase congruency; Spatio-temporal descriptor; Emotion recognition; Facial expression
spellingShingle Phase congruency; Spatio-temporal descriptor; Emotion recognition; Facial expression
Shojaeilangari, Seyedehsamaneh
Yau, Wei-Yun
Teoh, Eam Khwang
A novel phase congruency based descriptor for dynamic facial expression analysis
description Representation and classification of dynamic visual events in videos have been an active field of research. This work proposed a novel spatio-temporal descriptor based on phase congruency concept and applied it to recognize facial expression from video sequences. The proposed descriptor comprises histograms of dominant phase congruency over multiple 3D orientations to describe both spatial and temporal information of a dynamic event. The advantages of our proposed approach are local and dynamic processing, high accuracy, robustness to image scale variation, and illumination changes. We validated the performance of our proposed approach using the Cohn-Kanade (CK+) database where we achieved 95.44% accuracy in detecting six basic emotions. The approach was also shown to increase classification rates over the baseline results for the AVEC 2011 video subchallenge in detecting four emotion dimensions. We also validated its robustness to illumination and scale variation using our own collected dataset.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Shojaeilangari, Seyedehsamaneh
Yau, Wei-Yun
Teoh, Eam Khwang
format Article
author Shojaeilangari, Seyedehsamaneh
Yau, Wei-Yun
Teoh, Eam Khwang
author_sort Shojaeilangari, Seyedehsamaneh
title A novel phase congruency based descriptor for dynamic facial expression analysis
title_short A novel phase congruency based descriptor for dynamic facial expression analysis
title_full A novel phase congruency based descriptor for dynamic facial expression analysis
title_fullStr A novel phase congruency based descriptor for dynamic facial expression analysis
title_full_unstemmed A novel phase congruency based descriptor for dynamic facial expression analysis
title_sort novel phase congruency based descriptor for dynamic facial expression analysis
publishDate 2016
url https://hdl.handle.net/10356/81599
http://hdl.handle.net/10220/39591
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