Recognition by functional parts [function-based object recognition]
Rivlin, E.
Dickinson, S.J.
Rosenfeld, A.
Dept. of Comput. Sci., Technion-Israel Inst. of Technol., Haifa;
Abstract
We present an approach to function-based object recognition that
reasons about the functionality of an object's initiative parts. We
extend the popular “recognition by parts” shape recognition
framework to support “recognition, by functional parts”, by
combining a set of functional primitives and their relations with a set
of abstract volumetric shape primitives and their relations. Previous
approaches have relied on more global object features, often ignoring
the problem of object segmentation, and thereby restricting themselves
to range images of unoccluded scenes. We show how these shape primitives
and relations can be easily recovered from superquadric ellipsoids
which, in turn, can be recovered from either range or intensity images
of occluded scenes. Furthermore, the proposed framework supports both
unexpected (bottom-up) object recognition and expected (top-down) object
recognition. We demonstrate the approach on, a simple domain by
recognizing a restricted class of hand-tools from 2-D images
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