Toward an affect-sensitive multimodal human-computer interaction

By Maja Pantic, Léon J. M. Rothkrantz. Proceedings of the IEEE, 2003

898 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/1dff919e51c262c22630955972968f38ba385d8a

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Citations in the corpus

Social signal processing: Survey of an emerging domain (2009, background): “,[76][140][221]), the research on machine analysis of human social behaviour just started to attract the interest of the research community in computer science.”
Survey on Emotional Body Gesture Recognition (2018, neutral): “phony [137], video conferencing and stress-monitoring tool, violence detection [138], [139], [140], video surveillance [141], and animation or synthesis of life-like agents [139] and auto-”
Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns (2015, background): “potential applications of effective systems for emotion recognition, with some examples including affect-sensitive ManMachine-Interaction systems and auto tutors [12, 11, 29].”
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications (2010, background): “Nevertheless, when compared to an earlier review by Pantic and Rothkrantz [10], remarkable progress has been made along a number of dimensions.”
Facial expression recognition based on Local Binary Patterns: A comprehensive study (2009, background): “…The Netherlands b Department of Computer Science, Queen Mary, University of London, Mile End Road, London E1 4NS, UK a r t i c l e i n f o Article history: Received 12 June 2006 Received in revised form 14 February 2008 Accepted 16 August 2008 Keywords: Facial expression recognition Local…”
Human computing and machine understanding of human behavior: a survey (2006, background): “Hence, one could expect that in an automated analyzer of human behavior input signals should not be considered mutually independent and should not be combined only at the end of the intended analysis, as the majority of current studies do, but that they should be processed in a joint feature space a”
Fully Automatic Recognition of the Temporal Phases of Facial Actions (2012, background): “tion and facial muscle action detection [7]–[10].”
A Multimodal Database for Affect Recognition and Implicit Tagging (2012, background): “To develop and evaluate such applications, large collections of training and test data are needed [21], [22].”
Emotion recognition using brain activity (2008, background): “This communication can be done in a much more natural way [48], and open up new ways for computers to understand human behavior or meaning.”
Fully Automatic Facial Action Unit Detection and Temporal Analysis (2006, background): “For a good overview of the work done on AU and emotion detection from still images or face video the reader is referred to [9, 16].”