Applied Affective Computing: | ACM Books

Applied Affective ComputingJanuary 2022

Volume 41

January 2022

Authors:
Leimin Tian
Monash University
,
Sharon Oviatt
Monash University
,
Michal Muszynski
Carnegie Mellon University and University of Geneva
,
Brent C. Chamberlain
Utah State University
,
Jennifer Healey
Adobe Research, San Jose
,
Akane Sano
Rice University

Publisher:

Association for Computing Machinery
New York
NY
United States

ISBN:978-1-4503-9590-8

DOI:https://doi.org/10.1145/3502398

Published:07 February 2022

Pages:

308

Appears In:

ACM Books

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Bibliometrics

Abstract

Affective computing is a nascent field situated at the intersection of artificial intelligence with social and behavioral science. It studies how human emotions are perceived and expressed, which then informs the design of intelligent agents and systems that can either mimic this behavior to improve their intelligence or incorporate such knowledge to effectively understand and communicate with their human collaborators. Affective computing research has recently seen significant advances and is making a critical transformation from exploratory studies to real-world applications in the emerging research area known as applied affective computing.

This book offers readers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. It provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being. It also addresses ethical concerns related to affective computing and how to prevent misuse of the technology in research and applications. Further, this book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered.

For researchers and practitioners new to affective computing, this book will serve as an introduction to the field to help them in identifying new research topics or developing novel applications. For more experienced researchers and practitioners, the discussions in this book provide guidance for adopting a human-centered design and development approach to advance affective computing

Chapters

Preface

Introduction to Applied Affective Computing

Machine Learning Approaches for Applied Affective Computing

Multimodal Data Collection and Processing for Applied Affective Computing

Emotion Recognition in the Wild

Reinforcement Learning and Affective Computing

Synthesizing Natural and Believable Emotional Expressions

Emotion-aware Human–Robot Interaction and Social Robots

Affective Computing for Enhancing Well-Being

Applied Affective Computing in Built Environments

Addressing Ethical Issues of Affective Computing

Future of Affective Computing and Applied Affective Computing

Bibliography

Authors’ Biographies & Index

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