Toward Computational Model of Emotion from Individual Difference in Perceiving Facial Expressions

We propose a computational model for identifying emotional state of a facial expression from appraisal scores given by human observers utilizing their differences in perception. The appraisal model of human emotion is adopted as the basis of this evaluation process with appraisal variables as output...

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Published inPsychological studies Vol. 63; no. 3; pp. 266 - 275
Main Authors Gupta, Shakuntala, Biswal, Ramakrishna, Gupta, Supratim
Format Journal Article
LanguageEnglish
Published New Delhi Springer India 01.09.2018
Springer Nature B.V
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Abstract We propose a computational model for identifying emotional state of a facial expression from appraisal scores given by human observers utilizing their differences in perception. The appraisal model of human emotion is adopted as the basis of this evaluation process with appraisal variables as output. We investigated the performance for both categorical and continuous representation of the variables appraised by human observers. Analysis of the data exhibits higher degree of agreement between estimated Indian ratings and the available reference when these are rated through continuous domain. We also observed that emotional state with negative valence are influential in the perception of hybrid emotional state like ‘Surprise’, only when appraisal variables are labeled through categories of emotions. Thus, the proposed method has implications in developing software to detect emotion using appraisal variables in continuous domain, perceived from facial expression of an agent (or human subject). Further, this model can be customized to include cultural variability in recognizing emotions.
AbstractList We propose a computational model for identifying emotional state of a facial expression from appraisal scores given by human observers utilizing their differences in perception. The appraisal model of human emotion is adopted as the basis of this evaluation process with appraisal variables as output. We investigated the performance for both categorical and continuous representation of the variables appraised by human observers. Analysis of the data exhibits higher degree of agreement between estimated Indian ratings and the available reference when these are rated through continuous domain. We also observed that emotional state with negative valence are influential in the perception of hybrid emotional state like ‘Surprise’, only when appraisal variables are labeled through categories of emotions. Thus, the proposed method has implications in developing software to detect emotion using appraisal variables in continuous domain, perceived from facial expression of an agent (or human subject). Further, this model can be customized to include cultural variability in recognizing emotions.
Author Gupta, Shakuntala
Biswal, Ramakrishna
Gupta, Supratim
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  organization: Department of Electrical Engineering, NIT
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Keywords Appraisal variable
Facial expressions
Computational model
Kernel density estimation
Emotion perception
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RussellJAFehrBRelativity in the perception of emotion in facial expressionsJournal of Experimental Psychology: General1987116322323710.1037/0096-3445.116.3.223
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CohenJA coefficient of agreement for nominal scalesEducational and Psychological Measurement1960201374610.1177/001316446002000104
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References_xml – reference: JackREGarrodOGBYuHCaldaraRSchynsPGFacial expressions of emotion are not culturally universalPNAS USA2012109197241724410.1073/pnas.120015510922509011
– reference: Mesquita, B., Vissers, N., & De Leersnyder, J. (2015). Culture and amotion. In J. Wright & J. Berry (Eds.), International encyclopedia of social and behavioral sciences (pp. 542–549). New York: Elsevier.
– reference: MartinezADuSA model of the perception of facial expressions of emotion by humans: Research overview and perspectivesMachine Learning Research201213115891608
– reference: RobersonDDavidoffJBraisbyNSimilarity and categorisation: Neuropsychological evidence for a dissociation in explicit categorisation tasksCognition199971114210.1016/S0010-0277(99)00013-X10394708
– reference: Whissell, C . M. (1989). The dictionary of affect in language. In R. Plutchik & H. Kellerman (Eds.), Emotion: Theory, research, and experience (pp. 112–131). New York: Academic Press.
– reference: KvalsethTONote on cohen’s kappaPsychological Reports198965122322610.2466/pr0.1989.65.1.223
– reference: RussellJAFehrBRelativity in the perception of emotion in facial expressionsJournal of Experimental Psychology: General1987116322323710.1037/0096-3445.116.3.223
– reference: RobinsonDLBrain function, mental experience and personalityThe Netherlands Journal of Psychology2009641152167
– reference: ElfenbeinH AEisenkraftNThe relation between displaying and perceiving nonverbal cues of affect: A meta-analysis to solve an old mystery.Journal of Personality and Social Psychology201098230131810.1037/a001776620085402
– reference: WidenSCRussellJADifferentiation in preschooler’s categories of emotionEmotion201010565166110.1037/a001900521038948
– reference: ElfenbeinHABeaupréMGLévesqueMHessUToward a dialect theory: Cultural differences in the expression and recognition of posed facial expressionsEmotion20077113114610.1037/1528-3542.7.1.13117352569
– reference: ElfenbeinHAAmbadyNUniversals and cultural differences in recognizing emotionsCurrent Directions in Psychological Science200312515916410.1111/1467-8721.01252
– reference: Baldassarri, S., & Cerezo, E. (2012). Maxine: Embodied conversational agents for multimodal emotional communication. In N. Mukai (Ed.), Computer Graphics (pp. 195–212). Croatia: Intech.
– reference: ElfenbeinHAAmbadyNOn the universality and cultural specificity of emotion recognition: A meta-analysisPsychological Bulletin2002128220323510.1037/0033-2909.128.2.20311931516
– reference: Russell, J. A. (1995). Facial expressions of emotion: What lies beyond minimal universality? Psychological Bulletin, 118(3), 379–391.
– reference: LinJSpraragenMZydaMComputational models of emotion and cognitionAdvances in Cognitive Systems2012215976
– reference: CohenJA coefficient of agreement for nominal scalesEducational and Psychological Measurement1960201374610.1177/001316446002000104
– reference: SauterDAEisnerFEkmanPScottSKCross-cultural recognition of basic emotions through nonverbal emotional vocalizationsPNAS201010762408241210.1073/pnas.090823910620133790
– reference: BroekensJDeGrootDKostersWAFormal models of appraisal: Theory, specification, and computational modelCognitive Systems Research20089317319710.1016/j.cogsys.2007.06.007
– reference: Lyons, M., Akamatsu, S., Kamachi, M., & Gyoba, J. (1998). Coding facial expressions with gabor wavelets. In Third IEEE International Conference on Automatic Face and Gesture Recognition. IEEE, pp. 1–6.
– reference: MarsellaSGratchJComputationally modeling human emotionCommunications of the ACM20145712566710.1145/2631912
– reference: ZadraJRCloreGLEmotion and perception: The role of affective informationWIREs Cognitive Science20112667668510.1002/wcs.14722039565
– reference: BlaisCJackREScheepersCFisetDCaldaraRCulture shapes how we look at facesPLoS ONE2008381810.1371/journal.pone.0003022
– reference: BarrettLFMesquitaBGendronMContext in emotion perceptionCurrent Directions in Psychological Science201120528629010.1177/0963721411422522
– reference: EllsworthPCAppraisal theory: Old and new questionsEmotion Review20135212513110.1177/1754073912463617
– reference: BowmanAWAzzaliniAApplied smoothing techniques for data analysis1997OxfordClarendon Press
– reference: OrtonyACloreGLCollinsAThe cognitive structure of emotions1988CambridgeCambridge University Press10.1017/CBO9780511571299
– reference: RobersonDDamjanovicLPillingMCategorical perception of facial expressions: Evidence for a “category adjustment” modelMemory & Cognition20073571814182910.3758/BF03193512
– reference: EkmanPCordaroDWhat is meant by calling emotions basicEmotion Review20113436437010.1177/1754073911410740
– reference: CowieRDouglas-CowieETsapatsoulisNVotsisGKolliasSFellenzWTaylorJGEmotion recognition in human–computer interactionIEEE Signal Processing Magazine2001181328010.1109/79.911197
– reference: PhelpsEALingSCarrascoMEmotion facilitates perception and potentiates the perceptual benefit of attentionPsychological Sciences200617429229910.1111/j.1467-9280.2006.01701.x
– reference: GendronMLindquistKABarsalouLBarrettLFEmotion words shape emotion perceptsEmotion201212231432510.1037/a0026007223097174445832
– reference: ScottDWMultivariate density estimation20152Hoboken, NJWiley
– reference: YanXAndrewsTJYoungAWCultural similarities and differences in perceiving and recognizing facial expressions of basic emotionsJournal of Experimental Psychology: Human Perception and Performance201642342344026480247
– reference: Ekman, P. (1972). Universals and cultural differences in facial expressions of emotions. In Cole, J. (Ed.), Nebraska Symposium on Motivation (pp. 207–282). Lincoln, NB: University of Nebraska Press.
– reference: WatsonDGBlagroveETagging multiple emotional stimuli: Negative valence has little benefitJournal of Experimental Psychology: Human Perception and Performance201238378580322201468
– reference: Engelmann, J. B., & Pogosyan, M. (2013). Emotion perception across culture: The role of cognitive mechanisms. Frontiers in Psychology, 4, 118. https://doi.org/10.3389/fpsyg.2013.00118.
– reference: BarrettLFConstructing emotionPsychological Topics2011203359380
– reference: Lucey, P., Cohn, J. F., Kanade, T., Saragih, J., Ambadar, Z., & Matthews, I. (2010). The extended Cohn–Kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, (pp. 94–101). San Francisco, CA: IEEE.
– reference: Tian, Y., Kanade, T., & Cohn, J. F. (2011). Facial expression recognition. In S. Z. Li & A. K. Jain (Eds.), Handbook of face recognition (pp. 487–519). Springer: London.
– reference: WoolfolkAEducational psychology20069New YorkPearson Education
– reference: CohenJWeighted kappa: Nominal scale agreement with provision for scaled disagreement or partial creditPsychological Bulletin196870421322010.1037/h002625619673146
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Snippet We propose a computational model for identifying emotional state of a facial expression from appraisal scores given by human observers utilizing their...
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SubjectTerms Behavioral Science and Psychology
Culture
Decision making
Emotions
General Psychology
Human subjects
Perceptions
Personality and Social Psychology
Psychology
Research in Progress
Variables
Title Toward Computational Model of Emotion from Individual Difference in Perceiving Facial Expressions
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