Optical flow based analyses to detect emotion from human facial image data

被引：14

作者：

Besinger, Axel ^{[1
,2
]}

Sztynda, Tamara ^{[1
]}

Lal, Sara ^{[1
,4
]}

Duthoit, Carmen ^{[3
]}

Agbinya, Johnson ^{[2
]}

Jap, Budi ^{[1
]}

Eager, David ^{[2
]}

Dissanayake, Gamini ^{[2
,4
]}

机构：

[1] Univ Technol Sydney, Dept Med & Mol Biosci, Sydney, NSW 2007, Australia

[2] Univ Technol Sydney, Fac Engn, Sydney, NSW 2007, Australia

[3] Sydney W Area Hlth Serv, Div Analyt Labs, Penrith, NSW 2751, Australia

[4] Univ Technol Sydney, Ctr Intelligent Mechatron Syst, Sydney, NSW 2007, Australia

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期

关键词：

Emotion recognition; Facial expression recognition; Feature point tracking; Facial feature extraction; Motion extraction; EXPRESSION;

D O I：

10.1016/j.eswa.2010.05.063

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Artificial recognition of facial expression has attracted a lot of attention in the last few years and different facial expression detection methods have been developed. The current study uses a feature point tracking technique separately applied to the five facial image regions (eyebrows, eyes and mouth) to capture basic emotions. The used dataset contains a total 60 facial images from subject's different genders and nationality not wearing glasses and/or facial hair. Results show that the used point tracking algorithm separately applied to the five facial image regions can detect emotions in image sequences. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：8897 / 8902

页数：6

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