Abstract
This paper presents a computational framework for providing affective labels to real-life situations, called A-Situ. We first define an affective situation, as a specific arrangement of affective entities relevant to emotion elicitation in a situation. Then, the affective situation is represented as a set of labels in the valence-arousal emotion space. Based on psychological behaviors in response to a situation, the proposed framework quantifies the expected emotion evoked by the interaction with a stimulus event. The accumulated result in a spatiotemporal situation is represented as a polynomial curve called the affective curve, which bridges the semantic gap between cognitive and affective perception in real-world situations. We show the efficacy of the curve for reliable emotion labeling in real-world experiments, respectively concerning (1) a comparison between the results from our system and existing explicit assessments for measuring emotion, (2) physiological distinctiveness in emotional states, and (3) physiological characteristics correlated to continuous labels. The efficiency of affective curves to discriminate emotional states is evaluated through subject-dependent classification performance using bicoherence features to represent discrete affective states in the valence-arousal space. Furthermore, electroencephalography-based statistical analysis revealed the physiological correlates of the affective curves.
Highlights
Affective situation representation: We introduce a polynomial curve called the “affective curve,” which is a set of cumulative points on the valence-arousal emotional space over time in a situation and represents affective dynamics in real-world environments
We evaluated the performance of our system for labeling emotions compared with the labels rated by the self-assessment manikins (SAM)
The predicted labels obtained from our system have different interpretation from the SAM ratings by the Baseline I for rating real-world situations, the classifiers based on our system achieve similar performance to those based on the SAM ratings
Summary
Multiple studies have been proposed to understand emotion and identify the different types of emotions people experience. The two most widely accepted theories in affective intelligence are basic emotion and dimensional theories. Ekman and Plutchik proposed that core emotions have evolved through natural selection from categorical perspectives[8]. Ekman identified six basic emotional expressions: happiness, sadness, disgust, fear, surprise, and anger. Social functions became a threshold to distinguish between anger and disgust, and between fear and surprise. Plutchik proposed a wheel of emotions, which illustrates eight basic emotions: joy, trust, fear, surprise, sadness, anticipation, anger, and disgust
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