Sensitivity to genuine versus posed emotion specified in facial displays

McLellan, Tracey; Johnston, Lucy; Dalrymple‐Alford, John C.; Porter, Richard

doi:10.1080/02699930903306181

Cited by 93 publications

(118 citation statements)

References 47 publications

(54 reference statements)

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“…The effect of reliable AUs on the identification of emotion is less conclusive than their effect on perceived intensity of the emotion and on perceived authenticity, which suggests that reliable AUs might be more important in the assessment of intensity, genuineness, and trustworthiness of internal states than in the classification of these states in emotion categories. It also indicates that perceivers' sensitivity to subtle differences between posed and genuine emotional displays (Gosselin et al, 2002;McLellan et al, 2010) may be related to the activation of a subset of facial movements. Thus, although both versatile and reliable AUs would work together to create emotional expressions, our results suggest that reliable AUs contribute to making them look more authentic and more intense.…”

Section: Discussionmentioning

confidence: 99%

“…be used by perceivers to discriminate between both types of expression (McLellan, Johnston, Dalrymple-Alford, & Porter, 2010). Previous research using acted emotional portrayals showed that facial movements that are expected in the expression of a given emotion are more frequently used in the portrayals than facial movements that are not expected to be present in that emotion (Gosselin, Kirouac, & Doré, 1995).…”

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confidence: 99%

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Reliable facial muscle activation enhances recognizability and credibility of emotional expression.

Méhu

Mortillaro

Bänziger

et al. 2012

Emotion

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We tested Ekman's (2003) suggestion that movements of a small number of reliable facial muscles are particularly trustworthy cues to experienced emotion because they tend to be difficult to produce voluntarily. On the basis of theoretical predictions, we identified two subsets of facial action units (AUs): reliable AUs and versatile AUs. A survey on the controllability of facial AUs confirmed that reliable AUs indeed seem more difficult to control than versatile AUs, although the distinction between the two sets of AUs should be understood as a difference in degree of controllability rather than a discrete categorization. Professional actors enacted a series of emotional states using method acting techniques, and their facial expressions were rated by independent judges. The effect of the two subsets of AUs (reliable AUs and versatile AUs) on identification of the emotion conveyed, its perceived authenticity, and perceived intensity was investigated. Activation of the reliable AUs had a stronger effect than that of versatile AUs on the identification, perceived authenticity, and perceived intensity of the emotion expressed. We found little evidence, however, for specific links between individual AUs and particular emotion categories. We conclude that reliable AUs may indeed convey trustworthy information about emotional processes but that most of these AUs are likely to be shared by several emotions rather than providing information about specific emotions. This study also suggests that the issue of reliable facial muscles may generalize beyond the Duchenne smile.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Reliable facial muscle activation enhances recognizability and credibility of emotional expression.

Méhu

Mortillaro

Bänziger

et al. 2012

Emotion

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“…First, we establish norms for many of the stimuli from two popular databases that are widely used in the literature, the Pictures of Facial Affect (PoFA; Ekman & Friesen, 1976) and the Radboud Faces Database (RaFD; Langner et al, 2010), and for the only published set (the McLellan faces; as provided to us, T. McLellan, personal communication, November 24, 2010; see also McLellan et al, 2010) where the actual emotional state of the displayer has been verified (by self-report) for emotions other than happiness.…”

Section: Study Aims: Development Of Norms and New Stimulus Setsmentioning

confidence: 99%

“…Although the focus has mostly been on happy expressions (Ekman & Friesen, 1982;Frank, Ekman, & Friesen, 1993; for a review, see Gunnery & Ruben, 2016), more recent work has begun to include a broader range of emotions, asking questions such as: Can adults discriminate genuineness in facial expressions other than happiness (e.g., sadness, fear, Electronic supplementary material The online version of this article (doi:10.3758/s13428-016-0813-2) contains supplementary material, which is available to authorized users. disgust; Douglas, Porter, & Johnston, 2012;McLellan, Johnston, Dalrymple-Alford, & Porter, 2010)? Can children do the same (sadness, fear; Dawel, Palermo, O'Kearney, & McKone, 2015)?…”

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confidence: 99%

Perceived emotion genuineness: normative ratings for popular facial expression stimuli and the development of perceived-as-genuine and perceived-as-fake sets

et al. 2016

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In everyday social interactions, people's facial expressions sometimes reflect genuine emotion (e.g., anger in response to a misbehaving child) and sometimes do not (e.g., smiling for a school photo). There is increasing theoretical interest in this distinction, but little is known about perceived emotion genuineness for existing facial expression databases. We present a new method for rating perceived genuineness using a neutral-midpoint scale (-7 = completely fake; 0 = don't know; +7 = completely genuine) that, unlike previous methods, provides data on both relative and absolute perceptions. Normative ratings from typically developing adults for five emotions (anger, disgust, fear, sadness, and happiness) provide three key contributions. First, the widely used Pictures of Facial Affect (PoFA; i.e., Bthe Ekman faces^) and the Radboud Faces Database (RaFD) are typically perceived as not showing genuine emotion. Also, in the only published set for which the actual emotional states of the displayers are known (via self-report; the McLellan faces), percepts of emotion genuineness often do not match actual emotion genuineness. Second, we provide genuine/fake norms for 558 faces from several sources (PoFA, RaFD, KDEF, Gur, FacePlace, McLellan, News media), including a list of 143 stimuli that are event-elicited (rather than posed) and, congruently, perceived as reflecting genuine emotion. Third, using the norms we develop sets of perceived-as-genuine (from eventelicited sources) and perceived-as-fake (from posed sources) stimuli, matched on sex, viewpoint, eye-gaze direction, and rated intensity. We also outline the many types of research questions that these norms and stimulus sets could be used to answer.

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“…The major part of CK+ and CK Enhanced datasets contains posed facial expressions that may considerably differ from the spontaneous ones [31]. Spontaneous expressions, which may differ in intensity, timing, and co-occurrence with other actions [32], [5], [2].…”

Section: Study On Au12/au14 Intensity Estimation On Spontaneous Datamentioning

confidence: 99%

Continuous AU intensity estimation using localized, sparse facial feature space

Jeni

Girard

Cohn

et al. 2013

2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)

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Abstract-Most work in automatic facial expression analysis seeks to detect discrete facial actions. Yet, the meaning and function of facial actions often depends in part on their intensity. We propose a part-based, sparse representation for automated measurement of continuous variation in AU intensity. We evaluated its effectiveness in two publically available databases, CK+ and the soon to be released Binghamton high-resolution spontaneous 3D dyadic facial expression database. The former consists of posed facial expressions and ordinal level intensity (absent, low, and high). The latter consists of spontaneous facial expression in response to diverse, well-validated emotion inductions, and 6 ordinal levels of AU intensity.In a preliminary test, we started from discrete emotion labels and ordinal-scale intensity annotation in the CK+ dataset. The algorithm achieved state-of-the-art performance. These preliminary results supported the utility of the part-based, sparse representation. Second, we applied the algorithm to the more demanding task of continuous AU intensity estimation in spontaneous facial behavior in the Binghamton database. Manual 6-point ordinal coding and continuous measurement were highly consistent. Visual analysis of the overlay of continuous measurement by the algorithm and manual ordinal coding strongly supported the representational power of the proposed method to smoothly interpolate across the full range of AU intensity.

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Sensitivity to genuine versus posed emotion specified in facial displays

Abstract: To link to this Article: DOI: 10.1080/0269993090330618

Cited by 93 publications

References 47 publications

Reliable facial muscle activation enhances recognizability and credibility of emotional expression.

Reliable facial muscle activation enhances recognizability and credibility of emotional expression.

Perceived emotion genuineness: normative ratings for popular facial expression stimuli and the development of perceived-as-genuine and perceived-as-fake sets

Continuous AU intensity estimation using localized, sparse facial feature space

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