Abstract
The authors report the implementation and evaluation of a
function-based recognition system that takes an uninterrupted 3-D object
shape as its input and reasons to determine if the object belongs to the
superordinate category furniture, and if so, into which (sub)category it
falls. The system has analyzed over 250 input objects, and the results
largely agree with intuitive human interpretation of the objects. The
study confirms that a relatively small number of knowledge primitives
may be used as the basis for defining a relatively broad range of object
categories. The greatest derivation from intuitive human interpretation
occurs with objects that humans would not typically label as one of the
known categories defined, but which have some novel orientation in which
they could serve the function of one of these categories. This is
because the system uses a purely function-based definition of the object
category
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