Affective computing
Affective appraisal versus cognitive evaluation
Affective interactions
Integrating models of personality and emotions into lifelike characters
Affective interactions
Participatory Design: Principles and Practices
Participatory Design: Principles and Practices
Participatory design: the third space in HCI
The human-computer interaction handbook
To feel or not to feel: the role of affect in human-computer interaction
International Journal of Human-Computer Studies - Application of affective computing in humanComputer interaction
International Journal of Human-Computer Studies - Application of affective computing in humanComputer interaction
Emotion and sociable humanoid robots
International Journal of Human-Computer Studies - Application of affective computing in humanComputer interaction
Neural Networks - Special issue: Emotion and brain
Modeling naturalistic affective states via facial and vocal expressions recognition
Proceedings of the 8th international conference on Multimodal interfaces
Parameterized facial expression synthesis based on MPEG-4
EURASIP Journal on Applied Signal Processing
MPEG-4 facial expression synthesis
Personal and Ubiquitous Computing
Lifelike pedagogical agents and affective computing: an exploratory synthesis
Artificial intelligence today
Modeling emotions and other motivations in synthetic agents
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A domain-independent framework for modeling emotion
Cognitive Systems Research
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Affective computing has been an extremely active research and development area for some years now, with some of the early results already starting to be integrated in human-computer interaction systems. Driven mainly by research initiatives in Europe, USA and Japan and accelerated by the abundance of processing power and low-cost, unintrusive sensors like cameras and microphones, affective computing functions in an interdisciplinary fashion, sharing concepts from diverse fields, such as signal processing and computer vision, psychology and behavioral sciences, human-computer interaction and design, machine learning, and so on. In order to form relations between low-level input signals and features to high-level concepts such as emotions or moods, one needs to take into account the multitude of psychology and representation theories and research findings related to them and deploy machine learning techniques to actually form computational models of those. This chapter elaborates on the concepts related to affective computing, how these can be connected to measurable features via representation models and how they can be integrated into humancentric applications.