• DocumentCode
    3424513
  • Title

    The Interestingness of Images

  • Author

    Gygli, Michael ; Grabner, Herbert ; Riemenschneider, Hayko ; Nater, Fabian ; Van Gool, Luc

  • Author_Institution
    Comput. Vision Lab., ETH Zurich, Zurich, Switzerland
  • fYear
    2013
  • fDate
    1-8 Dec. 2013
  • Firstpage
    1633
  • Lastpage
    1640
  • Abstract
    We investigate human interest in photos. Based on our own and others\´ psychophysical experiments, we identify various cues for "interestingness", namely aesthetics, unusualness and general preferences. For the ranking of retrieved images, interestingness shows to be more appropriate than cues proposed earlier. Interestingness is correlated with what people believe they will remember. This is opposed to actual memorability, which is uncorrelated to both. We introduce a set of features computationally capturing the three main aspects of visual interestingness and build an interestingness predictor from them. Its performance is shown on three datasets with varying context, reflecting the prior knowledge of the viewers.
  • Keywords
    content-based retrieval; image processing; image retrieval; photography; aesthetics; content-based image retrieval; general preferences; human interest; image interestingness; interestingness predictor; memorability; photos; psychophysical experiments; retrieved images ranking; unusualness; viewer knowledge; visual interestingness; Context; Correlation; Databases; Histograms; Image color analysis; Psychology; Training; Human Interest; Image Classification; Image Retrival; Interestingness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision (ICCV), 2013 IEEE International Conference on
  • Conference_Location
    Sydney, VIC
  • ISSN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2013.205
  • Filename
    6751313