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Applied Affective Computing [Pehme köide]

  • Formaat: Paperback / softback, 308 pages, kõrgus x laius x paksus: 234x190x16 mm, kaal: 363 g
  • Sari: ACM Collection II
  • Ilmumisaeg: 28-Feb-2022
  • Kirjastus: Association of Computing Machinery,U.S.
  • ISBN-10: 1450395910
  • ISBN-13: 9781450395915
  • Formaat: Paperback / softback, 308 pages, kõrgus x laius x paksus: 234x190x16 mm, kaal: 363 g
  • Sari: ACM Collection II
  • Ilmumisaeg: 28-Feb-2022
  • Kirjastus: Association of Computing Machinery,U.S.
  • ISBN-10: 1450395910
  • ISBN-13: 9781450395915

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.

List of Figures
xvii
List of Tables
xxiii
Preface xxv
Acknowledgments xxvi
Chapter 1 Introduction to Applied Affective Computing
1(16)
1.1 Affective Computing
1(3)
1.2 Applied Affective Computing
4(5)
1.3 Book Overview and Highlights
9(4)
1.4 Contributions
13(4)
Chapter 2 Emotions as Studied in Psychology and Cognitive Science
17(12)
2.1 Theories of Emotion
17(5)
2.2 Emotion as an Adaptive Function
22(1)
2.3 Emotion as a Social Communicative Function
23(4)
2.4 Summary
27(2)
Chapter 3 Machine Learning Approaches for Applied Affective Computing
29(20)
3.1 Machine Learning for Affective Computing
30(1)
3.2 Deep Machine Learning for Affective Computing
31(1)
3.3 Multimodal Representation of Affect: Knowledge-inspired versus Data-driven Features
32(1)
3.4 Unimodal Features for Affect Recognition
32(8)
3.5 Multimodal Emotion-aware Systems
40(3)
3.6 Evaluation of Emotion-aware Systems
43(1)
3.7 Synthesis of Emotion and Emotional Behaviors
44(1)
3.8 Discussion
45(1)
3.9 Conclusion
46(3)
Chapter 4 Multimodal Data Collection and Processing for Applied Affective Computing
49(18)
4.1 Multimodal Data Collection
49(9)
4.2 Multimodal Data Processing
58(1)
4.3 Multimodal Data Fusion
59(6)
4.4 Conclusion and Future Work
65(2)
Chapter 5 Emotion Recognition in the Wild
67(14)
5.1 Modalities
68(2)
5.2 Deep Learning for Emotion Recognition in the Wild
70(2)
5.3 Emotion Representation in the Wild
72(1)
5.4 Evaluation of Affect Recognition in the Wild
73(2)
5.5 The Role of Context in Affect Recognition in the Wild
75(1)
5.6 The Role of Environment in Affect Recognition in the Wild
75(1)
5.7 Discussion
76(3)
5.8 Conclusion
79(2)
Chapter 6 Reinforcement Learning and Affective Computing
81(18)
6.1 Reinforcement Learning
82(6)
6.2 Affective Computing
88(2)
6.3 Extending the Reinforcement Learning Framework
90(6)
6.4 Conclusions
96(3)
Chapter 7 Synthesizing Natural and Believable Emotional Expressions
99(8)
7.1 Introduction
99(2)
7.2 Emotional Expression Models
101(1)
7.3 Synthesizing Emotional Expressions
102(1)
7.4 The Role of Agency
103(2)
7.5 Additional Considerations and Challenges
105(2)
Chapter 8 Emotion-aware Human--Robot Interaction and Social Robots
107(24)
8.1 Developing Emotion-aware Human--Robot Interaction Systems
107(2)
8.2 Improving Social Intelligence of a Robot by Addressing Social Errors in Human--Robot Interaction
109(1)
8.3 Case Study: Prompting Human Assistance in Human--Robot Collaboration Using Robots' Emotional Expressions
110(11)
8.4 Case Study: Understanding Users' Expectations of Robots in Public Spaces
121(5)
8.5 Challenges in Affective HRI
126(3)
8.6 Guidelines for Developing Affective HRI Systems and Social Robots
129(2)
Chapter 9 Affective Computing for Enhancing Well-Being
131(22)
9.1 Motivation
131(2)
9.2 Sensing and Analytics
133(2)
9.3 Examples of Well-Being Studies
135(4)
9.4 Sensing Beyond the Phone
139(5)
9.5 Actions and Interventions
144(4)
9.6 Conclusions
148(5)
Chapter 10 Applied Affective Computing in Built Environments
153(16)
10.1 Setting the Foundation Toward Emotionally Aware Planning and Design
153(3)
10.2 Case Study: Passive Responses to Urban Infrastructure
156(1)
10.3 Experimental Task
157(2)
10.4 Data
159(2)
10.5 Approach
161(3)
10.6 Results
164(2)
10.7 Conclusions
166(1)
10.8 Guidelines for Affective Computing in Built Environments
167(2)
Chapter 11 Addressing Ethical Issues of Affective Computing
169(18)
11.1 Ethical Concerns of Affective Computing
169(3)
11.2 A Fair System
172(3)
11.3 A Privacy-preserving System
175(3)
11.4 A Transparent System
178(2)
11.5 A Beneficial System
180(3)
11.6 A Responsible System
183(2)
11.7 Conclusion
185(2)
Chapter 12 Future of Affective Computing and Applied Affective Computing
187(18)
12.1 Applied Affective Computing: Guidelines for Best Practice
187(3)
12.2 Example Uses of the Guidelines
190(4)
12.3 Open Challenges and Future Directions
194(9)
12.4 Summary
203(2)
Bibliography 205(62)
Authors' Biographies 267(4)
Index 271
Leimin Tian is a postdoctoral research fellow at the Human-Centred AI Group of the Faculty of Information Technology and the HumanRobot Interaction Group of the Faculty of Engineering, Monash University. She received a M.Sc. in Artificial Intelligence in 2013 and a Ph.D. in Informatics in 2018 from the Institute for Language, Cognition and Computation at the School of Informatics, the University of Edinburgh. Her research interests include affective computing, humanrobot interaction, multimodal emotion recognition, multimodal behavioral analytics, and dialogue systems. For more information on Leimin's research, please see https://tianleimin.github.io/. Leimin has contributed to formulating the outline of this book and editing it, and is the lead author of Chapters 1, 2, 8, 11, and 12.

Sharon Oviatt is a professor at the Engineering Office of the Dean, Monash University. Her main areas of research are human-centered, multimodal, mobile, and educational interfaces. Sharon is an internationally recognized computer scientist, professor, and researcher known for her work in the field of humancomputer interaction on human-centered multimodal interface design and evaluation. She has published over 150 scientific publications in the HCI field and worked as a Professor of Computer Science, Psychology, and Linguistics at several different universities. She has served as an editor for several important HCI journals including Transactions on Interactive Intelligent Systems (TIIS), and she chaired the International Conference on Multimodal Interfaces in 2003. She is a former Professor and Co-Director at the Center for HumanComputer Communication (CHCC) in the Department of Computer Science at Oregon Health & Science University. She currently serves as the President and Chair of the Board of Directors of Incaa Designs, a non-profit with the aim of researching and designing new educational interfaces. She is also a Professor of HCI and Creative Technologies at Monash University in Melbourne, Australia. Much of her research is focused on examining the effectiveness of speech and pen interfaces in educational settings. For more information on Sharon's research, please see https://research.monash.edu/en/persons/sharonoviatt. Sharon has contributed to formulating the outline of this book and editing it, as well as co-authoring Chapters 1, 2, 8, 11, and 12.

Michal Muszynski is a postdoctoral research associate (SNSF fellowship holder) at the University of Geneva, Switzerland, and at Carnegie Mellon University, the United States. He carries out interdisciplinary research at the intersection of computer science, neuroscience, medicine, and psychology. He received his Ph.D. in Computer Science from the University of Geneva in 2018. His research interests are in the areas of multimodal machine learning, affective computing, multimedia analysis, healthcare, human behavior analysis, affective neuroscience, and signal processing. For more information on Michal's research, please see https://michal-muszynski.github.io/. Michal is the lead author of Chapters 3 and 5 of this book.

Brent Chamberlain is an Associate Professor at Utah State University in the department of Landscape Architecture and Environmental Planning. His research spans a wide variety of disciplines with a foundation for research in geovisualization, geospatial science, and environmental psychology. He is the co-director of the Visualization, Instrumentation and Virtual Interactive Design Laboratory. For more information on Brent's research, please see: http://laep.usu.edu/vivid/ and http://brentchamberlain.org/. Brent is the lead author of Chapters 7 and 10 of this book.

Jennifer Healey is a senior research scientist at Adobe. She is most passionate about finding ways to apply technology to solve real-world problems. Her current research focus is around understanding people's emotions in real-world situations by using machine learning algorithms to infer emotional states from sensed data. For more information on Jennifer's research, please see: https://www.linkedin.com/in/healeyjennifer. Jennifer is the lead author of Chapters 6 and 9 of this book.

Akane Sano is an Assistant Professor at Rice University, Department of Electrical Computer Engineering, Computer Science, and Bioengineering. She directs the Computational Wellbeing Group. Her research focuses on human sensing, data analysis and modeling, and intelligent system development for health, well-being, and performance. She is also a member of the Rice Scalable Health Labs. Her research spans the field of affective, ubiquitous, and wearable computing and biobehavioral sensing and analysis/modeling. Her research targets (1) the analysis and modeling of human ambulatory multimodal time series data including physiological, biological, and behavioral data and surveys for measuring, predicting, improving, and understanding human physiology and behavior and human factors such as health, well-being, and performance and (2) development of human-centered computing technologies for health, well-being, and performance. She has been working on developing tools, algorithms, and systems to measure, forecast, understand, and improve health and well-being using mobile and wearable sensors and devices in daily life settings, especially for measuring, predicting, and intervening/improving stress, mental health, sleep, and performance. She received her Ph.D. at MIT Media Lab and her M.Eng. and B.Eng. at Keio University, Japan. Before she joined Rice University, she was a Research Scientist in the Affective Computing Group at MIT Media Lab and a visiting scientist/lecturer at the People-Aware Computing Lab, Cornell University. Before she came to the United States, she was a researcher/engineer at Sony Corporation and worked on wearable computing, intelligent systems, and humancomputer interaction. For more information on Akane's research, please see: http://akane.sano.web.rice.edu/. Akane is the lead author of Chapter 4 and assisted on Chapter 9 of this book.