Fuzzy emotion recognition model for video sequences

M. Oussalah; S. Wang

doi:10.1109/IPTA.2012.6469574

Fuzzy emotion recognition model for video sequences

M. Oussalah
, S. Wang

Electronic, Electrical and Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

2 Citations (Scopus)

382 Downloads (Pure)

Abstract

Automatic facial expression recognition from video clips is a challenging task due to computational complexity, limitations of image analysis and subjectivity. This paper advocates a fuzzy based approach for emotion classification. On the other hand, several proposals have been put forward to enhance the pre-processing stage prior to the classification. This includes a combination of a boundary elliptical model for skin detection, adaptive thresholding, principal component analysis and use of cam-shift for face tracking. The performances of the developed system have been evaluated using TFEID and video clips and compared with Bayes' classifier.

Original language	English
Title of host publication	Image Processing Theory, Tools and Applications (IPTA), 2012 3rd International Conference on
Pages	127-132
DOIs	https://doi.org/10.1109/IPTA.2012.6469574
Publication status	Published - Oct 2012
Event	2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA) - Istanbul, Turkey, United Kingdom Duration: 15 Oct 2012 → 18 Oct 2012

Conference

Conference	2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)
Country/Territory	United Kingdom
Period	15/10/12 → 18/10/12

Access to Document

10.1109/IPTA.2012.6469574

FuzzyEmotion IPTA212 OussalahSubmitted manuscript, 703 KB

http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6469574

Cite this

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title = "Fuzzy emotion recognition model for video sequences",

abstract = "Automatic facial expression recognition from video clips is a challenging task due to computational complexity, limitations of image analysis and subjectivity. This paper advocates a fuzzy based approach for emotion classification. On the other hand, several proposals have been put forward to enhance the pre-processing stage prior to the classification. This includes a combination of a boundary elliptical model for skin detection, adaptive thresholding, principal component analysis and use of cam-shift for face tracking. The performances of the developed system have been evaluated using TFEID and video clips and compared with Bayes' classifier.",

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AB - Automatic facial expression recognition from video clips is a challenging task due to computational complexity, limitations of image analysis and subjectivity. This paper advocates a fuzzy based approach for emotion classification. On the other hand, several proposals have been put forward to enhance the pre-processing stage prior to the classification. This includes a combination of a boundary elliptical model for skin detection, adaptive thresholding, principal component analysis and use of cam-shift for face tracking. The performances of the developed system have been evaluated using TFEID and video clips and compared with Bayes' classifier.

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Fuzzy emotion recognition model for video sequences

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