cam a22 5 4500 317153277 CHVBK 20201009192931.0 m d cr |n |||||||| 140625s2014 gw |||| s 0 0|eng d 978-3-319-05491-9 978-3-319-05490-2 (print) 10.1007/978-3-319-05491-9 doi (SERSOL)ssj0001186540 (IDSSG)000655479 (WaSeSS)ssj0001186540 WaSeSS QH323.5 UYQP bicssc UYQV bicssc COM016000 bisacsh 570.15195 23 CH001A719D6FA41C2A2F8C1257F0700702575 iCapture Fu Yun editor Human-Centered Social Media Analytics [Elektronische Daten] edited by Yun Fu Cham Springer International Publishing Imprint: Springer 2014 1 online resource (VIII, 208 p. 97 illus., 51 illus. in color.) online resource text file PDF rda 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. Lizenzbedingungen können den Zugang einschränken. License restrictions may limit access. 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. Computer science Data mining Artificial intelligence Computer vision Biometrics SpringerLink (Online service) Printed edition 9783319054902 https://link.springer.com/10.1007/978-3-319-05491-9 Uni Basel: Volltext BK020053 XK020053 XK020000 Springer Computer Science eBooks 2014 English/International E-Books von 360MarcUpdates noalma ids I IDSSG HSG HSG ONL HONL000655479 IDSBB A145 A145 145VT IDSBB 100 1- Fu Yun editor IDSBB 710 2- SpringerLink (Online service) IDSBB 776 08 Printed edition 9783319054902 IDSBB 856 40 https://link.springer.com/10.1007/978-3-319-05491-9 Uni Basel: Volltext IDSSG 700 1- Fu Yun IDSSG 856 4- https://doi.org/10.1007/978-3-319-05491-9 Full text for the University of St. Gallen SWISSBIB 317153277