Abstract

Deformable models can be widely used to approximate object;. from collected data points, but most algorithms can only handle geometrically and topologically simple objects. They are inadequate for objects with deep cavities or multi- part objects, or when more than one object is in the scene. We propose an approach which can fit simultaneously more than one surface to approximate multiple topological- ly complex objects. We use (I) the residual data points, (2) the bad parts of the fitting surface, and (3) appropriate Boolean operations. We then present an algorithm to con- struct an analytical surface representation, based on the el- ements detected. The global representation of an object, in terms of elements and their connection, takes the form of B- spline ad Btzier surfaces. A Btzier surface is employed to connect different elements, and the connecting surjiace itserf conforms to the data points nearby through energy minimi- zation. This way, we achieve G' continuity surfaces even for multipart objects. We present results on complex synthetic and real da- ta. The system proceeds automatically without human in- teraction or any prior knowledge on the topology of the underlying object. eywords snakes, range image, deformable model, B-spline, Bkz- ier surface, blending surface, segmentation.

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