We are investigating the feasibility of functional description as a knowledge representation for recognition of 3-D objects. This description can be used to recognize classes and identify subclasses of known categories of objects even if the specific object has never been encountered previously. Having conceptual models therefore allows the system the flexibility to learn new exemplars of a known class of object. The major goal of this work is to develop a knowledge representation which defines a class of objects in terms of its function. The system will interpret the possible functionality of an object by reasoning about its 3-D form. By using this more abstract conceptual representation instead of a concrete geometric representation, we feel we can reduce the potential search space involved in the recognition process and broaden the recognition capabilities of the vision system.