THE DEVELOPMENT OF A FACIAL-AFFECT RECOGNITION SYSTEM FOR APPLICATION IN HUMAN-ROBOT INTERACTION SCENARIOS

被引：0

作者：

Schacter, David ^{[1
]}

Wang, Christopher ^{[1
]}

Nejat, Goldie ^{[1
]}

Benhabib, Beno ^{[1
]}

机构：

[1] Univ Toronto, Dept Mech & Ind Engn, Toronto, ON, Canada

来源：

PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2011, VOL 2, PTS A AND B | 2012年

关键词：

SUPPORT VECTOR REGRESSION; EXPRESSION RECOGNITION; CIRCUMPLEX MODEL; APPROXIMATION;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents a non-contact unique automated affect recognition system that identifies human facial expressions and classifies them using Support Vector Regression (SVR) into affective states based on a pleasure-arousal two-dimensional model of affect. By utilizing a continuous two-dimensional model, rather than a traditional discrete categorical model for affect, the proposed system captures complex and ambiguous emotions that are prevalent in real-world scenarios. Our aim is to incorporate the proposed recognition system in robots engaged in human-robot interaction (HRI) scenarios. Namely, the system can be utilized by a robot to recognize, in real-time, spontaneous natural facial expressions of a variety of individuals in response to environmental and interactive stimuli. Preliminary experiments demonstrate the system's ability to recognize affect from a number of individuals displaying different facial expressions.

引用

页码：865 / 873

页数：9

共 37 条

[1]

Al-Hamadi A, 2009, LECT NOTES COMPUT SC, V5337, P228, DOI 10.1007/978-3-642-02345-3_23

[2] A real-time automated system for the recognition of human facial expressions [J].

Anderson, K ;

McOwan, PW .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2006, 36 (01) :96-105

[3]

[Anonymous], 2003, 2003 C COMPUTER VISI, DOI DOI 10.1109/CVPRW.2003.10057

[4]

[Anonymous], 2000, NEURAL INFORM PROCES

[5]

[Anonymous], 2003, EMOTIONS REVEALED RE

[6]

[Anonymous], 1980, THEORIES EMOTION, DOI [DOI 10.1016/B978-0-12-558701-3.50007-7, 10.1016/b978-0-12-558701-3.50007-7]

[7]

CAO J, 2008, INT S ADV VIS COMP, V5359, P450

[8] Multilevel support vector regression analysis to identify condition-specific regulatory networks [J].

Chen, Li ;

Xuan, Jianhua ;

Riggins, Rebecca B. ;

Wang, Yue ;

Hoffman, Eric P. ;

Clarke, Robert .

BIOINFORMATICS, 2010, 26 (11) :1416-1422

[9] Robust support vector regression networks for function approximation with outliers [J].

Chuang, CC ;

Su, SF ;

Jeng, JT ;

Hsiao, CC .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (06) :1322-1330

[10] Analysis of support vector regression for approximation of complex engineering analyses [J].

Clarke, SM ;

Griebsch, JH ;

Simpson, TW .

JOURNAL OF MECHANICAL DESIGN, 2005, 127 (06) :1077-1087

← 1 2 3 4 →