Journal ArticleDOI
Automatic Emotion Recognition Based on Body Movement Analysis: A Survey
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TLDR
This survey describes emerging techniques and modalities related to emotion recognition based on body movement as well as recent advances in automatic emotion recognition and describes application areas and notation systems and explains the importance of movement segmentation.Abstract:
Humans are emotional beings, and their feelings influence how they perform and interact with computers One of the most expressive modalities for humans is body posture and movement, which researchers have recently started exploiting for emotion recognition This survey describes emerging techniques and modalities related to emotion recognition based on body movement, as well as recent advances in automatic emotion recognition It also describes application areas and notation systems and explains the importance of movement segmentation It then discusses unsolved problems and provides promising directions for future research The Web extra (a PDF file) contains tables with additional information related to the articleread more
Citations
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Journal ArticleDOI
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
TL;DR: The emotion recognition methods based on multi-channel EEG signals as well as multi-modal physiological signals are reviewed and the correlation between different brain areas and emotions is discussed.
Journal ArticleDOI
Social touch in human–computer interaction
TL;DR: It is argued that ICT mediated or generated social touch can (a) intensify the perceived social presence of remote communication partners and (b) enable computer systems to more effectively convey affective information.
Book ChapterDOI
Survey on AI-Based Multimodal Methods for Emotion Detection
Catherine Marechal,Dariusz Mikołajewski,Krzysztof Tyburek,Piotr Prokopowicz,Lamine Bougueroua,Corinne Ancourt,Katarzyna Wegrzyn-Wolska +6 more
TL;DR: This paper investigates the possibility of automated emotion representation, recognition and prediction its state-of-the-art and main directions for further research, focusing on the impact of emotion analysis and state of the arts of multimodal emotion detection.
Journal ArticleDOI
Emotion Recognition From Body Movement
TL;DR: A novel two-layer feature selection framework for emotion classification from a comprehensive list of body movement features is introduced, which achieved a very high emotion recognition rate outperforming all of the state-of-the-art methods.
Journal ArticleDOI
Human–Robot Facial Expression Reciprocal Interaction Platform: Case Studies on Children with Autism
TL;DR: A robotic platform has been developed for reciprocal interaction consisting of two main phases, namely as Non-structured and Structured interaction modes, and the effect and acceptability of the platform have been investigated on autistic children between 3 and 7 years old.
References
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Journal ArticleDOI
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