High-level CAD Model Acquisition from Range Images

Automatic extraction of CAD descriptions which are ultimately intended for human manipulation requires the accurate inference of geometric and topological information. We present a system which applies segmentation techniques from computer vision to automatically extract CAD models from range images of parts with curved surfaces. The output of the system is a B-rep of the object which is suitable for further manipulation in a modelling system. The segmentation process is an improvement upon Besl and Jain's variable-order surface tting 1 , extracting general quadric surfaces and planes from the data, with a postprocessing stage to identify surface intersections and to extract a B-rep from the segmented image. We present results on a variety of machined objects, which illustrate the high-level nature of the acquired models, and discuss the numerical accuracy (feature sizes and separations) and the correctness of structural inferences of the system.