A relational model for describing three-dimensional objects has been designed and implemented as part of a database system. The models which provide rough descriptions to be used at the top level of a hierarchy for describing objects, were designed for initial matching attempts on an unknown object. The descriptions are in terms of the set of simple parts of the objects. Simple parts can be sticks (long, thin parts), plates (flat, wide parts) , and blobs (parts that have three significant dimensions). The relations include an attribute-value table for global properties of the object, the properties of the simple parts, binary connection and support relationships, ternary connection relationships, parallel relationships, perpendicular relationships, and binary constraints. An important use of the system is to characterize the similarity and differences between three-dimensional objects. Toward this end, we have defined a measure of relational similarity between three-dimensional object models and a measure of feature similarity, based only on Euclidean distance between attribute-value tables. In a series of experiments, we compare the results of using the two different similarity measures and conclude that the relational similarity is much more powerful than the feature similarity and should be used when grouping the objects in the database for fast access
