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Beyond pure static shape in function-based object recognition

There has recently been growing interest in exploiting the concept of reasoning about function for object recognition. In a function-based approach to object recognition, recognition of an object means labeling it as belonging to some category of objects according to the function that it could serve. The few function-based recognition systems which have so far been described in the literature have all assumed that the input to the problem is a pure static shape description. By `pure' shape we mean that the only object property that the systems have reasoned about is their abstract shape. By `static' shape we mean that the systems have reasoned about an object from only a single (assumed rigid) abstract shape instance. This paper discusses some of the issues which must be addressed in extending the function-based approach to handle non-shape properties (such as material properties) and dynamic shape descriptions.