People watching: human actions as a cue for single view geometry
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Scene semantics from long-term observation of people
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Graspable parts recognition in man-made 3d shapes
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
View-Invariant object detection by matching 3d contours
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Tagging-by-search: automatic image region labeling using gaze information obtained from image search
Proceedings of the 19th international conference on Intelligent User Interfaces
Object-object interaction affordance learning
Robotics and Autonomous Systems
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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 appearance-based 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.