• 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