• DocumentCode
    3495305
  • Title

    On the role of context in probabilistic models of visual saliency

  • Author

    Bruce, Neil D B ; Kornprobst, Pierre

  • Author_Institution
    INRIA, Sophia Antipolis, France
  • fYear
    2009
  • fDate
    7-10 Nov. 2009
  • Firstpage
    3089
  • Lastpage
    3092
  • Abstract
    In recent years, many principled probabilistic definitions for the determination of visual saliency have been proposed. Moreover, there has been increased focus on the role of context in the determination of visual salience. Prior efforts have shed some light on how context may help in predicting the location of, or presence of features associated with an object in the context of detection or recognition. Nevertheless, there remains a variety of manners in which context may be exploited towards providing better judgements of salient content. In this light, we investigate the role of context in the probabilistic determination of salience while presenting a number of potential avenues for future research.
  • Keywords
    feature extraction; probability; feature detection; feature recognition; probabilistic models; visual saliency; Animals; Context modeling; Filters; Independent component analysis; Layout; Object detection; Proposals; Roads; Statistics; Streaming media; attention; context; image statistics; saliency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2009 16th IEEE International Conference on
  • Conference_Location
    Cairo
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-5653-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2009.5414483
  • Filename
    5414483