Automatic, Dimensional and Continuous Emotion Recognition

By Hatice Gunes, Maja Pantic. International Journal of Synthetic Emotions, 2010

460 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/b466645f0e80ba31cb50d2b5dd241f9db6f7c34e

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

In Experimental and Cognitive Psychology

Citations in the corpus

Meta-Analysis of the First Facial Expression Recognition Challenge (2012, background): “Recently, there has been more interest in the automatic recognition of dimensional affect [22], [23], [46].”
Multimodal Emotion Recognition using Deep Learning (2021, background): “However, emotional variations can be observed in physiological signals for a very short period of around 315seconds [73].”
Emotion representation, analysis and synthesis in continuous space: A survey (2011, background): “, between −50 and +50 [46], or between −1 and +1 (divided into a number of levels) [14].”
Multimodal Continuous Emotion Recognition with Data Augmentation Using Recurrent Neural Networks (2018, background): “Continuous emotion recognition as a function of time assigns an emotional value to every frame in a sequence [1, 2], usually consisting of arousal, valence, and dominance [3].”
Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space (2011, methodology): “Compared to the works introduced in Tables 1 and 2, and surveyed in [27], the methodology introduced in this paper 1) presents the first approach toward automatic, dimensional, and continuous affect prediction based on facial expression, shoulder gesture, and audio cues, and 2) proposes a framework…”
Memory Fusion Network for Multi-view Sequential Learning (2018, background): “These emotions are categorized as basic emotions (Ekman 1992) and continuous emotions (Gunes 2010).”
Affective Body Expression Perception and Recognition: A Survey (2013, background): “While there is a clear need to create technologies that exploit the body as an affective communication modality, there is a less clear understanding on how these systems should be built, validated, and compared [27], [28].”
Wavelet-based emotion recognition system using EEG signal (2017, methodology): “Unfortunately, there is not a fixed window size to be used for achieving optimal emotion recognition in the literature [16], and thus in the current work, temporal windows of 2 and 4 s were used for EEG signals.”
Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing (2012, unknown): “…valence, arousal, and dominance—and pioneering efforts toward automatic dimensional and continuous emotion recognition have been recently proposed [99], a number of crucial issues need to be addressed first if these approaches to automatic dimensional and continuous emotion recognition are to be…”