• DocumentCode
    3172347
  • Title

    Camera Shooting Location Recommendations for Landmarks in Geo-space

  • Author

    Ying Zhang ; Zimmermann, Raphael

  • Author_Institution
    Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2013
  • fDate
    14-16 Aug. 2013
  • Firstpage
    172
  • Lastpage
    181
  • Abstract
    Taking photos of landmarks is a favorite and popular way for travellers to keep memories of places they have visited. Community-contributed photo collections, such as on Flickr, provide us an opportunity to gain a more in-depth understanding of a landmark´s visual appeal. While much current research is focusing on recommending which representative photos should be selected from such pervasive photo sources, our work aims to find out where a visitor can capture his or her own, beautiful and personal photo of a queried landmark. We believe that this aspect of helping users to take memorable photos has not been well studied. We propose a method to recommend a list of shooting locations that have the utmost potential to capture appealing photos for a landmark of interest. A Gaussian Mixture Model based clustering approach is applied to the camera locations from an existing photo repository, generating a set of regions each of which covers an area with sufficient semantics, e.g., a route section. The scores and ranks among these camera locations are evaluated through multiple criteria, including their potential for better visual aesthetics, overall social attractiveness, popularity, etc. Additionally, we investigate the temporal characteristics of these locations by considering the spatio-temporal space. A number of different recommendations are generated from these results, such as the best camera positions at different times throughout a single day, or the best visiting time in the same spatial area. Subjective evaluation studies have been conducted, which indicate that our work can generate promising results.
  • Keywords
    Gaussian processes; cameras; mixture models; query processing; recommender systems; Flickr; Gaussian mixture model-based clustering approach; appealing photo; camera positions; camera shooting location recommendation; community-contributed photo collections; geospace; landmark photos; landmark visual appeal; landmarks; location temporal characteristics; pervasive photo sources; photo repository; queried landmark; route section; social attractiveness; visual aesthetics; Cameras; Feature extraction; Gaussian mixture model; Image color analysis; Three-dimensional displays; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS), 2013 IEEE 21st International Symposium on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1526-7539
  • Type

    conf

  • DOI
    10.1109/MASCOTS.2013.25
  • Filename
    6730760