Provides a survey of next-generation social computational methodologies, from fundamentals to state-of-the-art techniques
Includes perspectives from an international and interdisciplinary selection of pre-eminent authorities
Presents balanced coverage of both detailed theoretical analysis and real-world applications
This book provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation.
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Utilizing the ubiquity of social media in modern society, the emerging interdisciplinary field of social computing offers the promise of important human-centered applications.
Human-Centered Social Media Analytics provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. The collected chapters present a range of different viewpoints examining the various possibilities and challenges to machine understanding of humans in a social context.
Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation; requires no prior background knowledge of the area.
This authoritative text/reference will be a valuable resource for researchers and graduate students interested in social media and networking, computer vision and biometrics, big data, and HCI. Practitioners in these fields, as well as in image processing and computer graphics, will also find the book of great interest.
Part I: Social Relationships in Human-Centered Media
Bridging Human-Centered Social Media Content across Web Domains
Suman Deb Roy, Tao Mei, and Wenjun Zeng
Learning Social Relations from Videos: Features, Models and Analytics
Lei Ding and Alper Yilmaz
Community Understanding in Location-Based Social Networks
Yi-Liang Zhao, Qiang Cheng, Shuicheng Yan, Daqing Zhang, and Tat-Seng Chua
Social Role Recognition for Human Event Understanding
Vignesh Ramanathan, Bangpeng Yao, and Li Fei-Fei
Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities
Aditya Khosla, Bangpeng Yao, and Li Fei-Fei
Part II: Human Attributes in Social Media Analytics
Recognizing People in Social Context
Gang Wang, Andrew Gallagher, Jiebo Luo, and David Forsyth
Female Facial Beauty Attribute Recognition and Editing
Jinjun Wang, Yihong Gong, and Douglas Gray
Facial Age Estimation: A Data Representation PerspectiveXin Geng
Identity and Kinship Relations in Group Pictures
Ming Shao, Siyu Xia, and Yun Fu
Recognizing Occupations through Probabilistic Models: A Social View
Ming Shao and Yun Fu
Utilizing the ubiquity of social media in modern society, the emerging interdisciplinary field of social computing offers the promise of important human-centered applications.
Human-Centered Social Media Analytics provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. The collected chapters present a range of different viewpoints examining the various possibilities and challenges to machine understanding of humans in a social context.
Topics and features:
- Includes perspectives from an international and interdisciplinary selection of pre-eminent authorities
- Presents balanced coverage of both detailed theoretical analysis and real-world applications
- Examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications
- Reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities
- Discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation
- Requires no prior background knowledge of the area
This authoritative text/reference will be a valuable resource for researchers and graduate students interested in social media and networking, computer vision and biometrics, big data, and HCI. Practitioners in these fields, as well as in image processing and computer graphics, will also find the book of great interest.
Dr. Yun Fu is an assistant professor in the Department of Electrical and Computer Engineering at Northeastern University, Boston, MA, USA, where he is the founder of the Synergetic Media Learning (SMILE) Lab.
"Human-Centered Social Media Analytics focuses on the novel social computational methodologies that are being developed to investigate social media data. ... Scholars, both new and established, should consider reading ... to gain an understanding of the questions they should pursue and the challenges they must overcome as they strive to advance big data and social media analytics research.” (Pratyush Bharati, Interfaces, Vol. 47 (3), May-June, 2017)
This book provides a timely and unique survey of next-generation social computational methodologies. discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation.
This book provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation.
Part I: Social Relationships in Human-Centered Media.- Bridging Human-Centered Social Media Content across Web Domains.- Learning Social Relations from Videos.- Community Understanding in Location-Based Social Networks.- Social Role Recognition for Human Event Understanding.- Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities.- Part II: Human Attributes in Social Media Analytics.- Recognizing People in Social Context.- Female Facial Beauty Attribute Recognition and Editing.- Facial Age Estimation.- Identity and Kinship Relations in Group Pictures.- Recognizing Occupations through Probabilistic Models.
"Human-Centered Social Media Analytics focuses on the novel social computational methodologies that are being developed to investigate social media data. ... Scholars, both new and established, should consider reading ... to gain an understanding of the questions they should pursue and the challenges they must overcome as they strive to advance big data and social media analytics research." (Pratyush Bharati, Interfaces, Vol. 47 (3), May-June, 2017)
Inhaltsverzeichnis
Part I: Social Relationships in Human-Centered Media.- Bridging Human-Centered Social Media Content across Web Domains.- Learning Social Relations from Videos.- Community Understanding in Location-Based Social Networks.- Social Role Recognition for Human Event Understanding.- Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities.- Part II: Human Attributes in Social Media Analytics.- Recognizing People in Social Context.- Female Facial Beauty Attribute Recognition and Editing.- Facial Age Estimation.- Identity and Kinship Relations in Group Pictures.- Recognizing Occupations through Probabilistic Models.
Klappentext
This book provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation.
Provides a survey of next-generation social computational methodologies, from fundamentals to state-of-the-art techniques
Includes perspectives from an international and interdisciplinary selection of pre-eminent authorities
Presents balanced coverage of both detailed theoretical analysis and real-world applications
Includes supplementary material: sn.pub/extras
