Applied Affective Computing /
Tian, Leimin
Applied Affective Computing / Leimin Tian, Sharon Oviatt, Michal Muszynski, Brent C. Chamberlain, Jennifer Healey, Akane Sano. - First Edition - 1 PDF (xxvi, 282 pages) LuaTEX - ACM books, #41 2374-6777 ; . - ACM books - Collection 2 ; #41. .
Preface 1 Introduction to Applied Affective Computing -- 1.1 Affective Computing -- 1.2 Applied Affective Computing -- 1.3 Book Overview and Highlights -- 1.4 Contributions 2 Emotions as Studied in Psychology and Cognitive Science -- 2.1 Theories of Emotion -- 2.2 Emotion as an Adaptive Function -- 2.3 Emotion as a Social Communicative Function -- 2.4 Summary 3 Machine Learning Approaches for Applied Affective Computing -- 3.1 Machine Learning for Affective Computing -- 3.2 Deep Machine Learning for Affective Computing -- 3.3 Multimodal Representation of Affect: Knowledge-inspired versus Data-driven Features -- 3.4 Unimodal Features for Affect Recognition -- 3.5 Multimodal Emotion-aware Systems -- 3.6 Evaluation of Emotion-aware Systems -- 3.7 Synthesis of Emotion and Emotional Behaviors -- 3.8 Discussion -- 3.9 Conclusion 4 Multimodal Data Collection and Processing for Applied Affective Computing -- 4.1 Multimodal Data Collection -- 4.2 Multimodal Data Processing -- 4.3 Multimodal Data Fusion -- 4.4 Conclusion and Future Work 5 Emotion Recognition in the Wild -- 5.1 Modalities-- 5.2 Deep Learning for Emotion Recognition in the Wild -- 5.3 Emotion Representation in the Wild -- 5.4 Evaluation of Affect Recognition in the Wild -- 5.5 The Role of Context in Affect Recognition in the Wild -- 5.6 The Role of Environment in Affect Recognition in the Wild -- 5.7 Discussion -- 5.8 Conclusion 6 Reinforcement Learning and Affective Computing -- 6.1 Reinforcement Learning -- 6.2 Affective Computing -- 6.3 Extending the Reinforcement Learning Framework -- 6.4 Conclusions 7 Synthesizing Natural and Believable Emotional Expressions -- 7.1 Introduction -- 7.2 Emotional Expression Models -- 7.3 Synthesizing Emotional Expressions -- 7.4 The Role of Agency -- 7.5 Additional Considerations and Challenges 8 Emotion-aware Human-Robot Interaction and Social Robots -- 8.1 Developing Emotion-aware Human-Robot Interaction Systems -- 8.2 Improving Social Intelligence of a Robot by Addressing Social Errors in Human-Robot Interaction -- 8.3 Case Study: Prompting Human Assistance in Human-Robot Collaboration Using Robots' Emotional Expressions -- 8.4 Case Study: Understanding Users' Expectations of Robots in Public Spaces -- 8.5 Challenges in Affective HRI -- 8.6 Guidelines for Developing Affective HRI Systems and Social Robots 9 Affective Computing for Enhancing Well-Being -- 9.1 Motivation -- 9.2 Sensing and Analytics -- 9.3 Examples of Well-Being Studies -- 9.4 Sensing Beyond the Phone -- 9.5 Actions and Interventions -- 9.6 Conclusions 10 Applied Affective Computing in Built Environments -- 10.1 Setting the Foundation Toward Emotionally Aware Planning and Design -- 10.2 Case Study: Passive Responses to Urban Infrastructure -- 10.3 Experimental Task -- 10.4 Data -- 10.5 Approach -- 10.6 Results -- 10.7 Conclusions -- 10.8 Guidelines for Affective Computing in Built Environments 11 Addressing Ethical Issues of Affective Computing -- 11.1 Ethical Concerns of Affective Computing -- 11.2 A Fair System -- 11.3 A Privacy-preserving System -- 11.4 A Transparent System -- 11.5 A Beneficial System -- 11.6 A Responsible System -- 11.7 Conclusion 12 Future of Affective Computing and Applied Affective Computing -- 12.1 Applied Affective Computing: Guidelines for Best Practice -- 12.2 Example Uses of the Guidelines -- 12.3 Open Challenges and Future Directions -- 12.4 Summary Bibliography Author's Biographies Index
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Mode of access: World Wide Web
System requirements: Adobe Acrobat Reader
3502398 9781450395939 9781450395922
10.1145/3502398 doi
Applied Affective Computing (Computer Science)
Electronic books.
Applied Affective Computing / Leimin Tian, Sharon Oviatt, Michal Muszynski, Brent C. Chamberlain, Jennifer Healey, Akane Sano. - First Edition - 1 PDF (xxvi, 282 pages) LuaTEX - ACM books, #41 2374-6777 ; . - ACM books - Collection 2 ; #41. .
Preface 1 Introduction to Applied Affective Computing -- 1.1 Affective Computing -- 1.2 Applied Affective Computing -- 1.3 Book Overview and Highlights -- 1.4 Contributions 2 Emotions as Studied in Psychology and Cognitive Science -- 2.1 Theories of Emotion -- 2.2 Emotion as an Adaptive Function -- 2.3 Emotion as a Social Communicative Function -- 2.4 Summary 3 Machine Learning Approaches for Applied Affective Computing -- 3.1 Machine Learning for Affective Computing -- 3.2 Deep Machine Learning for Affective Computing -- 3.3 Multimodal Representation of Affect: Knowledge-inspired versus Data-driven Features -- 3.4 Unimodal Features for Affect Recognition -- 3.5 Multimodal Emotion-aware Systems -- 3.6 Evaluation of Emotion-aware Systems -- 3.7 Synthesis of Emotion and Emotional Behaviors -- 3.8 Discussion -- 3.9 Conclusion 4 Multimodal Data Collection and Processing for Applied Affective Computing -- 4.1 Multimodal Data Collection -- 4.2 Multimodal Data Processing -- 4.3 Multimodal Data Fusion -- 4.4 Conclusion and Future Work 5 Emotion Recognition in the Wild -- 5.1 Modalities-- 5.2 Deep Learning for Emotion Recognition in the Wild -- 5.3 Emotion Representation in the Wild -- 5.4 Evaluation of Affect Recognition in the Wild -- 5.5 The Role of Context in Affect Recognition in the Wild -- 5.6 The Role of Environment in Affect Recognition in the Wild -- 5.7 Discussion -- 5.8 Conclusion 6 Reinforcement Learning and Affective Computing -- 6.1 Reinforcement Learning -- 6.2 Affective Computing -- 6.3 Extending the Reinforcement Learning Framework -- 6.4 Conclusions 7 Synthesizing Natural and Believable Emotional Expressions -- 7.1 Introduction -- 7.2 Emotional Expression Models -- 7.3 Synthesizing Emotional Expressions -- 7.4 The Role of Agency -- 7.5 Additional Considerations and Challenges 8 Emotion-aware Human-Robot Interaction and Social Robots -- 8.1 Developing Emotion-aware Human-Robot Interaction Systems -- 8.2 Improving Social Intelligence of a Robot by Addressing Social Errors in Human-Robot Interaction -- 8.3 Case Study: Prompting Human Assistance in Human-Robot Collaboration Using Robots' Emotional Expressions -- 8.4 Case Study: Understanding Users' Expectations of Robots in Public Spaces -- 8.5 Challenges in Affective HRI -- 8.6 Guidelines for Developing Affective HRI Systems and Social Robots 9 Affective Computing for Enhancing Well-Being -- 9.1 Motivation -- 9.2 Sensing and Analytics -- 9.3 Examples of Well-Being Studies -- 9.4 Sensing Beyond the Phone -- 9.5 Actions and Interventions -- 9.6 Conclusions 10 Applied Affective Computing in Built Environments -- 10.1 Setting the Foundation Toward Emotionally Aware Planning and Design -- 10.2 Case Study: Passive Responses to Urban Infrastructure -- 10.3 Experimental Task -- 10.4 Data -- 10.5 Approach -- 10.6 Results -- 10.7 Conclusions -- 10.8 Guidelines for Affective Computing in Built Environments 11 Addressing Ethical Issues of Affective Computing -- 11.1 Ethical Concerns of Affective Computing -- 11.2 A Fair System -- 11.3 A Privacy-preserving System -- 11.4 A Transparent System -- 11.5 A Beneficial System -- 11.6 A Responsible System -- 11.7 Conclusion 12 Future of Affective Computing and Applied Affective Computing -- 12.1 Applied Affective Computing: Guidelines for Best Practice -- 12.2 Example Uses of the Guidelines -- 12.3 Open Challenges and Future Directions -- 12.4 Summary Bibliography Author's Biographies Index
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Mode of access: World Wide Web
System requirements: Adobe Acrobat Reader
3502398 9781450395939 9781450395922
10.1145/3502398 doi
Applied Affective Computing (Computer Science)
Electronic books.