Some Objects Are More Equal Than Others: Measuring and Predicting Importance

  • Merrielle Spain
  • Pietro Perona
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5302)


We observe that everyday images contain dozens of objects, and that humans, in describing these images, give different priority to these objects. We argue that a goal of visual recognition is, therefore, not only to detect and classify objects but also to associate with each a level of priority which we call ‘importance’. We propose a definition of importance and show how this may be estimated reliably from data harvested from human observers. We conclude by showing that a first-order estimate of importance may be computed from a number of simple image region measurements and does not require access to image meaning.


Human Observer Measured Importance Median Order Human Annotation Spatial Pyramid Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Merrielle Spain
    • 1
  • Pietro Perona
    • 1
  1. 1.California Institute of TechnologyUSA

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