Fuzzy emotion: a natural approach to automatic facial expression recognition from psychological perspective using fuzzy system

被引:20
作者
Liliana, Dewi Yanti [1 ]
Basaruddin, T. [1 ]
Widyanto, M. Rahmat [1 ]
Oriza, Imelda Ika Dian [2 ]
机构
[1] Univ Indonesia, Fac Comp Sci, Kampus UI, Depok, Indonesia
[2] Univ Indonesia, Fac Psychol, Kampus UI, Depok, Indonesia
关键词
Artificial intelligence; Affective computing; Emotion recognition; Facial expression; Fuzzy emotion; Fuzzy system;
D O I
10.1007/s10339-019-00923-0
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Many studies in automatic facial expression recognitions merely limit their focus on recognizing basic emotions, ignoring the fact that humans show various emotions in their daily life. Moreover, from psychological perspective humans express multiple emotions simultaneously. Up to now, researchers recognize two basic emotions at the same time, called mixed emotions. Nevertheless, the mixed emotion still does not reflect how humans express the emotion naturally. This paper advances the concept of mixed emotion into a generalized fuzzy emotion. Fuzzy emotion captures multiple emotions in a single image using fuzzy inference engine. We propose a fuzzy emotion framework which consists of processing system and knowledge system. The processing system extracts facial expression parameters, and the knowledge system employs a fuzzy knowledge-based engine, elicited from the psychologist knowledge to recognize facial expressions. Some advantages are offered: (1) no facial template comparison; (2) no training efforts needed; (3) moreover, fuzzy emotion can recognize ambiguous facial expressions adaptively. The experiment gives a recognition result with the highest accuracy rate of 0.90. A research agenda for future study of mixed emotion recognition is proposed.
引用
收藏
页码:391 / 403
页数:13
相关论文
共 24 条
[1]   An online fuzzy-based approach for human emotions detection: An overview on the human cognitive model of understanding and generating multimodal actions [J].
Aly, Amir ;
Tapus, Adriana .
Springer Tracts in Advanced Robotics, 2015, 106 :185-212
[2]   Facial Expression Recognition Using Eigenspaces [J].
Chakrabarti, Debasmita ;
Dutta, Debtanu .
FIRST INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE: MODELING TECHNIQUES AND APPLICATIONS (CIMTA) 2013, 2013, 10 :755-761
[3]   Emotion Recognition From Facial Expressions and Its Control Using Fuzzy Logic [J].
Chakraborty, Aruna ;
Konar, Amit ;
Chakraborty, Uday Kumar ;
Chatterjee, Amita .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2009, 39 (04) :726-743
[4]   Active appearance models [J].
Cootes, TF ;
Edwards, GJ ;
Taylor, CJ .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2001, 23 (06) :681-685
[5]   Compound facial expressions of emotion [J].
Du, Shichuan ;
Tao, Yong ;
Martinez, Aleix M. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2014, 111 (15) :E1454-E1462
[6]   AN ARGUMENT FOR BASIC EMOTIONS [J].
EKMAN, P .
COGNITION & EMOTION, 1992, 6 (3-4) :169-200
[7]  
Ekman P, 2003, Unmasking the Face: A Guide to Recognizing Emotions from Facial Clues
[8]   A novel fuzzy facial expression recognition system based on facial feature extraction from color face images [J].
Ilbeygi, Mahdi ;
Shah-Hosseini, Hamed .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2012, 25 (01) :130-146
[9]   BASIC EMOTIONS, RELATIONS AMONG EMOTIONS, AND EMOTION COGNITION RELATIONS [J].
IZARD, CE .
PSYCHOLOGICAL REVIEW, 1992, 99 (03) :561-565
[10]  
Kamachi Miyuki, 1997, The japanese female facial expression (jaffe) database