DocumentCode
103764
Title
Large-Scale Geosocial Multimedia [Guest editorial]
Author
Rongrong Ji ; Yi Yang ; Sebe, Nicu ; Aizawa, K. ; Liangliang Cao
Volume
21
Issue
3
fYear
2014
fDate
July-Sept. 2014
Firstpage
7
Lastpage
9
Abstract
With the advance of the Web 2.0 era came an explosive growth of geographical multimedia data shared on social network websites such as Flickr, YouTube, Facebook, and Zooomr. Location-aware media description, modeling, learning, and recommendation in pervasive social media analytics have become a key focus of the recent research in computer vision, multimedia, and signal processing societies. A new breed of multimedia applications that incorporates image/video annotation, visual search, content mining and recommendation, and so on may revolutionize the field. Combined with the popularity of location-aware social multimedia, location context data makes traditionally challenging problems more tractable. This special issue brings together active researchers to share recent progress in this exciting area. This issue highlights the latest developments in large-scale multiple evidence-based learning for geosocial multimedia computing and identifies several key challenges and potential innovations.
Keywords
mobile computing; multimedia computing; social networking (online); geographical multimedia data; geosocial multimedia computing; location context data; location-aware social multimedia; pervasive social media analytics; social network Websites; Blogs; Geographic information systems; Geography; Geospatial analysis; Information services; Media; Multimedia communication; Social network services; Special issues and sections; Streaming media; Videos; geolocation; geosocial multimedia; landmark analysis; large-scale data; multimedia; multimedia applications; multimedia research; multimedia search; visual search;
fLanguage
English
Journal_Title
MultiMedia, IEEE
Publisher
ieee
ISSN
1070-986X
Type
jour
DOI
10.1109/MMUL.2014.43
Filename
6861914
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