Robust anger: Recognition of deteriorated dynamic bodily emotion expressions

Visch, Valentijn; Goudbeek, Martijn; Mortillaro, Marcello

doi:10.1080/02699931.2013.865595

Cited by 14 publications

(17 citation statements)

References 21 publications

(27 reference statements)

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“…These results are also in good accordance with recent work showing that angry body postures are detected more rapidly than happy body postures in an analogue of the face-in-a-crowd effect (Gilbert, Martin, & Coulson, 2011). Our findings also complement the research by Visch et al (2014) who found that recognition of anger from bodily expressions is highly robust with respect to stimulus degradation and more robust than recognition of fear, despair and joy.…”

Section: Discussionsupporting

confidence: 94%

“…Interestingly, in the latter study, facial expressions of anger were not well detected from a distance despite the obvious advantage of detecting threat from a distance. However, natural viewing conditions include a body which may better convey anger distally due to its larger size and broad dynamic patterns (Dael et al, 2012(Dael et al, , 2013 Recent work using dynamic expressions compared the recognisability of face and body cues across different emotions and increasing degrees of deteriorated viewing conditions (Visch, Goudbeek, & Mortillaro, 2014). Specifically, participants viewed emotional displays from intact videos, silhouettes with details, broad forms with no details or light point coordinates.…”

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confidence: 99%

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Contributions of facial expressions and body language to the rapid perception of dynamic emotions

Martínez

Falvello

Aviezer

et al. 2015

Cognition and Emotion

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Correctly perceiving emotions in others is a crucial part of social interactions. We constructed a set of dynamic stimuli to determine the relative contributions of the face and body to the accurate perception of basic emotions. We also manipulated the length of these dynamic stimuli in order to explore how much information is needed to identify emotions. The findings suggest that even a short exposure time of 250 milliseconds provided enough information to correctly identify an emotion above the chance level. Furthermore, we found that recognition patterns from the face alone and the body alone differed as a function of emotion. These findings highlight the role of the body in emotion perception and suggest an advantage for angry bodies, which, in contrast to all other emotions, were comparable to the recognition rates from the face and may be advantageous for perceiving imminent threat from a distance.

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Section: Discussionsupporting

confidence: 94%

mentioning

confidence: 99%

Contributions of facial expressions and body language to the rapid perception of dynamic emotions

Martínez

Falvello

Aviezer

et al. 2015

Cognition and Emotion

View full text Add to dashboard Cite

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“…In contrast, a fearful expression was marked by forearm activity, followed by an equally strong involvement of shoulders and biceps, while activity of the triceps is quite low (see Figure 5). Considering the function of the muscles, these findings are in line with previous descriptions of angry and fearful movements, such as raising the forearms to the trunk or stretching the arms downward with palms held up (anger) and lifting the arms with the hands held up protectively with the palms outward (fear) (De Meijer, 1989; Wallbott, 1998; Sawada et al, 2003; Coulson, 2004; Kleinsmith et al, 2006; Kessous et al, 2010; Dael et al, 2012b). See Figure 1 for examples of these movements in the stimuli.…”

Section: Discussionsupporting

confidence: 90%

The Body Action Coding System II: muscle activations during the perception and expression of emotion

Veld

Boxtel

Gelder

2014

Front. Behav. Neurosci.

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Research into the expression and perception of emotions has mostly focused on facial expressions. Recently, body postures have become increasingly important in research, but knowledge on muscle activity during the perception or expression of emotion is lacking. The current study continues the development of a Body Action Coding System (BACS), which was initiated in a previous study, and described the involvement of muscles in the neck, shoulders and arms during expression of fear and anger. The current study expands the BACS by assessing the activity patterns of three additional muscles. Surface electromyography of muscles in the neck (upper trapezius descendens), forearms (extensor carpi ulnaris), lower back (erector spinae longissimus) and calves (peroneus longus) were measured during active expression and passive viewing of fearful and angry body expressions. The muscles in the forearm were strongly active for anger expression and to a lesser extent for fear expression. In contrast, muscles in the calves were recruited slightly more for fearful expressions. It was also found that muscles automatically responded to the perception of emotion, without any overt movement. The observer's forearms responded to the perception of fear, while the muscles used for leaning backwards were activated when faced with an angry adversary. Lastly, the calf responded immediately when a fearful person was seen, but responded slower to anger. There is increasing interest in developing systems that are able to create or recognize emotional body language for the development of avatars, robots, and online environments. To that end, multiple coding systems have been developed that can either interpret or create bodily expressions based on static postures, motion capture data or videos. However, the BACS is the first coding system based on muscle activity.

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“…Several previous works support the importance of anger expressed via body motion: Pichon and colleagues have shown that a response to anger expression results in even more activation of defense mechanisms (“fight or flight”) than a response to fear expressions when the perceiver is the target of the anger (Pichon et al, 2009). A similar tendency is discussed in a recent study by Visch et al (2014), where recognition of anger expressed in the body motion was the most robust under various stimuli degradation conditions (including a condition where only parts of the upper body were portrayed). Others have found that a bias toward anger is even more pronounced in violent offenders (Kret and Gelder, 2013).…”

Section: Discussionsupporting

confidence: 83%

Emotion categorization of body expressions in narrative scenarios

et al. 2014

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Humans can recognize emotions expressed through body motion with high accuracy even when the stimuli are impoverished. However, most of the research on body motion has relied on exaggerated displays of emotions. In this paper we present two experiments where we investigated whether emotional body expressions could be recognized when they were recorded during natural narration. Our actors were free to use their entire body, face, and voice to express emotions, but our resulting visual stimuli used only the upper body motion trajectories in the form of animated stick figures. Observers were asked to perform an emotion recognition task on short motion sequences using a large and balanced set of emotions (amusement, joy, pride, relief, surprise, anger, disgust, fear, sadness, shame, and neutral). Even with only upper body motion available, our results show recognition accuracy significantly above chance level and high consistency rates among observers. In our first experiment, that used more classic emotion induction setup, all emotions were well recognized. In the second study that employed narrations, four basic emotion categories (joy, anger, fear, and sadness), three non-basic emotion categories (amusement, pride, and shame) and the “neutral” category were recognized above chance. Interestingly, especially in the second experiment, observers showed a bias toward anger when recognizing the motion sequences for emotions. We discovered that similarities between motion sequences across the emotions along such properties as mean motion speed, number of peaks in the motion trajectory and mean motion span can explain a large percent of the variation in observers' responses. Overall, our results show that upper body motion is informative for emotion recognition in narrative scenarios.

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Robust anger: Recognition of deteriorated dynamic bodily emotion expressions

Cited by 14 publications

References 21 publications

Contributions of facial expressions and body language to the rapid perception of dynamic emotions

Contributions of facial expressions and body language to the rapid perception of dynamic emotions

The Body Action Coding System II: muscle activations during the perception and expression of emotion

Emotion categorization of body expressions in narrative scenarios

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