The focus of the research has been on the definition of abstraction tools for deriving high-level descriptions of complex shape models. A key objective in research on shape-based modelling is to enhance traditional approaches to surface modelling through the definition of representations that are closer to our semantic coding of shape perception. Surface reconstruction techniques can be used to faithfully reproduce complex shape models of existing or virtual objects, which may be thought of as digital mock-ups to be visualized or analyzed using appropriate software. If, on the one hand, geometric representations are necessary for their approximation function, on the other, it is desirable to communicate with the model using higher-level abstractions, directly connected with specific properties of the shape. For example, when describing a landscape in words we would use terms such as mountainous , or expressions such as many ridges and ravines .
Reverse engineering is a good example of an interesting application field for our approach.
Digitizing machines usually perform sampling along predefined directions, sections or profiles, which induce at least a partial ordering in the data set. Shape-based techniques are especially efficient in this context since structural features of the underlying surface can be easily detected by analysing the configuration of points along the sampling directions. Reconstruction can thus be performed a posteriori with respect to the recognition of a rough shape skeleton. This is shown in Figure 1, where the approximating triangulation is fitted to the recognized structural features. IMA has also signed an important research contract with Monolith Ltd, Tokyo, within the framework of a programme funded by private and public Japanese research organizations, for the development of a terrain modelling system based on the topological and semantic structure of natural surfaces.