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The MPI emotional body expressions database for narrative scenarios.

Volkova E, de la Rosa S, Bülthoff HH, Mohler B - PLoS ONE (2014)

Bottom Line: We report the results of physical motion properties analysis and of an emotion categorisation study.The motion sequences along with the accompanying information are made available in a searchable MPI Emotional Body Expression Database.We hope that this database will enable researchers to study expression and perception of naturally occurring emotional body expressions in greater depth.

View Article: PubMed Central - PubMed

Affiliation: Department of Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Graduate School of Neural & Behavioural Sciences, Tübingen, Germany.

ABSTRACT
Emotion expression in human-human interaction takes place via various types of information, including body motion. Research on the perceptual-cognitive mechanisms underlying the processing of natural emotional body language can benefit greatly from datasets of natural emotional body expressions that facilitate stimulus manipulation and analysis. The existing databases have so far focused on few emotion categories which display predominantly prototypical, exaggerated emotion expressions. Moreover, many of these databases consist of video recordings which limit the ability to manipulate and analyse the physical properties of these stimuli. We present a new database consisting of a large set (over 1400) of natural emotional body expressions typical of monologues. To achieve close-to-natural emotional body expressions, amateur actors were narrating coherent stories while their body movements were recorded with motion capture technology. The resulting 3-dimensional motion data recorded at a high frame rate (120 frames per second) provides fine-grained information about body movements and allows the manipulation of movement on a body joint basis. For each expression it gives the positions and orientations in space of 23 body joints for every frame. We report the results of physical motion properties analysis and of an emotion categorisation study. The reactions of observers from the emotion categorisation study are included in the database. Moreover, we recorded the intended emotion expression for each motion sequence from the actor to allow for investigations regarding the link between intended and perceived emotions. The motion sequences along with the accompanying information are made available in a searchable MPI Emotional Body Expression Database. We hope that this database will enable researchers to study expression and perception of naturally occurring emotional body expressions in greater depth.

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Emotion frequency distribution across consistency levels.(A) Histogram of consistency rates across motion sequences. The minimally possible consistency is always equal to one divided by the number of observations for the given stimulus and multiplied by two because there have to be at least least two observers assigning the same category to the stimuli to form a modal value. (B) Distribution of perceived emotions across categories with a consistency rate of 0.3 or more. (C) Distribution of perceived emotions across categories with a consistency rate of 0.5 or more. (D) Distribution of perceived emotions across categories with a consistency rate of 0.7 or more.
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pone-0113647-g004: Emotion frequency distribution across consistency levels.(A) Histogram of consistency rates across motion sequences. The minimally possible consistency is always equal to one divided by the number of observations for the given stimulus and multiplied by two because there have to be at least least two observers assigning the same category to the stimuli to form a modal value. (B) Distribution of perceived emotions across categories with a consistency rate of 0.3 or more. (C) Distribution of perceived emotions across categories with a consistency rate of 0.5 or more. (D) Distribution of perceived emotions across categories with a consistency rate of 0.7 or more.

Mentions: The consistency is useful if the researcher wants to investigate the perception of emotions from body motion, for instance, to identify motion sequences or emotion categories that are perceived similarly by different observers. Our database organisation makes it easy to extract motion sequences with user-selected perceived categories and/or motion sequences with defined consistency rates. Figure 4 (A) shows the distribution of consistency rates across motion sequences perceived as non-neutral, showing that 0.3 is the most frequent consistency rate. Applying three cut-off levels (0.3, 0.5 and 0.7) we show the frequency of ten non-neutral emotion categories that include motion sequences with the cut-off consistency rate or higher (Figure 4 B, C, D). Motion sequences included in Figure 4C are a subset of motion sequences from Figure 4B and motion sequences from Figure 4D are a subset of motion sequences from Figure 4B and Figure 4C. Anger and sadness are always the most frequent perceived emotion categories, indicating that the observes of the corresponding motion sequences were in high agreement with each other. On the contrary, surprise, relief and disgust are the least frequent and are not even present in Figure 4D, meaning that though these categories formed the modal value in the observers' responses for certain motion sequences, the latter were not numerous and the number of responses falling into the categories was never more than half of the total responses available.


The MPI emotional body expressions database for narrative scenarios.

Volkova E, de la Rosa S, Bülthoff HH, Mohler B - PLoS ONE (2014)

Emotion frequency distribution across consistency levels.(A) Histogram of consistency rates across motion sequences. The minimally possible consistency is always equal to one divided by the number of observations for the given stimulus and multiplied by two because there have to be at least least two observers assigning the same category to the stimuli to form a modal value. (B) Distribution of perceived emotions across categories with a consistency rate of 0.3 or more. (C) Distribution of perceived emotions across categories with a consistency rate of 0.5 or more. (D) Distribution of perceived emotions across categories with a consistency rate of 0.7 or more.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4252031&req=5

pone-0113647-g004: Emotion frequency distribution across consistency levels.(A) Histogram of consistency rates across motion sequences. The minimally possible consistency is always equal to one divided by the number of observations for the given stimulus and multiplied by two because there have to be at least least two observers assigning the same category to the stimuli to form a modal value. (B) Distribution of perceived emotions across categories with a consistency rate of 0.3 or more. (C) Distribution of perceived emotions across categories with a consistency rate of 0.5 or more. (D) Distribution of perceived emotions across categories with a consistency rate of 0.7 or more.
Mentions: The consistency is useful if the researcher wants to investigate the perception of emotions from body motion, for instance, to identify motion sequences or emotion categories that are perceived similarly by different observers. Our database organisation makes it easy to extract motion sequences with user-selected perceived categories and/or motion sequences with defined consistency rates. Figure 4 (A) shows the distribution of consistency rates across motion sequences perceived as non-neutral, showing that 0.3 is the most frequent consistency rate. Applying three cut-off levels (0.3, 0.5 and 0.7) we show the frequency of ten non-neutral emotion categories that include motion sequences with the cut-off consistency rate or higher (Figure 4 B, C, D). Motion sequences included in Figure 4C are a subset of motion sequences from Figure 4B and motion sequences from Figure 4D are a subset of motion sequences from Figure 4B and Figure 4C. Anger and sadness are always the most frequent perceived emotion categories, indicating that the observes of the corresponding motion sequences were in high agreement with each other. On the contrary, surprise, relief and disgust are the least frequent and are not even present in Figure 4D, meaning that though these categories formed the modal value in the observers' responses for certain motion sequences, the latter were not numerous and the number of responses falling into the categories was never more than half of the total responses available.

Bottom Line: We report the results of physical motion properties analysis and of an emotion categorisation study.The motion sequences along with the accompanying information are made available in a searchable MPI Emotional Body Expression Database.We hope that this database will enable researchers to study expression and perception of naturally occurring emotional body expressions in greater depth.

View Article: PubMed Central - PubMed

Affiliation: Department of Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Graduate School of Neural & Behavioural Sciences, Tübingen, Germany.

ABSTRACT
Emotion expression in human-human interaction takes place via various types of information, including body motion. Research on the perceptual-cognitive mechanisms underlying the processing of natural emotional body language can benefit greatly from datasets of natural emotional body expressions that facilitate stimulus manipulation and analysis. The existing databases have so far focused on few emotion categories which display predominantly prototypical, exaggerated emotion expressions. Moreover, many of these databases consist of video recordings which limit the ability to manipulate and analyse the physical properties of these stimuli. We present a new database consisting of a large set (over 1400) of natural emotional body expressions typical of monologues. To achieve close-to-natural emotional body expressions, amateur actors were narrating coherent stories while their body movements were recorded with motion capture technology. The resulting 3-dimensional motion data recorded at a high frame rate (120 frames per second) provides fine-grained information about body movements and allows the manipulation of movement on a body joint basis. For each expression it gives the positions and orientations in space of 23 body joints for every frame. We report the results of physical motion properties analysis and of an emotion categorisation study. The reactions of observers from the emotion categorisation study are included in the database. Moreover, we recorded the intended emotion expression for each motion sequence from the actor to allow for investigations regarding the link between intended and perceived emotions. The motion sequences along with the accompanying information are made available in a searchable MPI Emotional Body Expression Database. We hope that this database will enable researchers to study expression and perception of naturally occurring emotional body expressions in greater depth.

Show MeSH
Related in: MedlinePlus