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Slide Circumplex Multidimensional
Emotion Detection
Challenges in emotion recognition today Real-life is not like a movie – people rarely show very expressive faces. Most of the time people are neutral, exhibiting very subtle expressions.

A single label cannot capture non-basic complex expressions with variations in emotions or intensity.
Circumplex Model of Affect Opsis uses the Circumplex Model of Affect to study Valence and Arousal ratings for emotion analysis from facial expressions to voice tone.

The model holds that all emotions can be described as a linear combination of two underlying neurophysiological systems (Arousal and Valence), with all emotions shading imperceptibly from one into another along the contour of the two-dimensional circumplex.

The technology addresses major issues in the current emotion recognition. We do not use prototypical models, but rather, a psychologically-plausible dimensional analysis across the Arousal and Valence attributes:

Arousal is an attribute that describes how energetic or not an emotion/expression is

Valence on the other hand describes the how positive or negative an emotion/expression is

A wide range of emotions can be represented with different Arousal/Valence values
Versus the Seven Basic Labelling Circumplex model can meaningfully describe in terms of a circular array of variables and the correlation structure of several psychological constructs. The model has gained increasing acknowledgment and popularity of use in psychology methodologies and data-analytics.

It is far superior than 7 basic labellings (surprised, sad, afraid, neutral, disgusted, angry, happy) which lack contextualisation as it is a biased selection of attributes with stereotypes and prejudices ingrained using pictures or videos for training.
Useful Insights from Circumplex Model We enable instantaneous measurements of spontaneous reactions from individuals.

Data pertaining to trends of emotional attributes over time and aggregated statistics is displayed in real-time.

For groups, we provide comparative analytics to identify how different people react to different situations.

For larger crowds, we measure and extract aggregated statistics from anyone involved.

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Enhance Devices to Understand Emotion

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