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What Makes a Chair a Chair?

H. Grabner, J. Gall, and L. Van Gool
In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
2011

Abstract

Many object classes are primarily defined by their functions. However, this fact has been left largely unexploited by visual object categorization or detection systems. We propose a method to learn an affordance detector. It identifies locations in the 3d space which “support” the particular function. Our novel approach “imagines” an actor performing an action typical for the target object class, instead of relying purely on the visual object appearance. So, function is handled as a cue complementary to appearance, rather than being a consideration after appearance-based detection. Experimental results are given for the functional category “sitting”. Such affordance is tested on a 3d representation of the scene, as can be realistically obtained through SfM or depth cameras. In contrast to appearancebased object detectors, affordance detection requires only very few training examples and generalizes very well to other sittable objects like benches or sofas when trained on a few chairs.


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@InProceedings{eth_biwi_00829,
  author = {H. Grabner and J. Gall and and L. Van Gool},
  title = {What Makes a Chair a Chair?},
  booktitle = {In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2011},
  keywords = {}
}