@article{Elazary_Itti08jov,
  title = {Interesting objects are visually salient},
  author = {L. Elazary and L. Itti},
  abstract = {How do we decide which objects in a visual scene are more interesting? While intuition may point toward high-level object recognition and cognitive processes, here we investigate the contributions of a much simpler process, low-level visual saliency. We used the LabelMe database (24,863 photographs with 74,454 manually outlined objects) to evaluate how often interesting objects were among the few most salient locations predicted by a computational model of bottom-up attention. In 43\% of all images the model's predicted most salient location falls within a labeled region (chance 21\%). Furthermore, in 76\% of the images (chance 43\%), one or more of the top three salient locations fell on an outlined object, with performance leveling off after six predicted locations. The bottom-up attention model has neither notion of object nor notion of semantic relevance. Hence, our results indicate that selecting interesting objects in a scene is largely constrained by low-level visual properties rather than solely determined by higher cognitive processes.},
  journal = {Journal of Vision},
  volume = {8},
  number = {3:3},
  pages = {1-15},
  year = {2008},
  month = {Mar},
  type = {td;mod;cv;sc},
  file = {http://ilab.usc.edu/publications/doc/Elazary_Itti08jov.pdf},
  if = {2006 impact factor: 3.753},
}