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Machine Vision Tools for CAGD

In this paper, the problem of constructing geometric models from data provided by 3-D imaging sensors is addressed. Such techniques allow for rapid modeling of sculptured free-form shapes and generation of geometric models for existing parts. In order for a complete data set to be obtained, multiple images, each from a different viewpoint, have to be merged. A technique stemming from the Iterative Closest Point (ICP) method for estimating the relative transformations among the viewpoints is developed. Computational solutions are provided for estimating shape from noisy sensory measurements using representations that conform with commonly used representations from Computer Aided Geometric Design (CAGD). In particular, NURBS and triangular surface representations are applied in shape estimation. The surface approximations are refined by the algorithms to meet a user-defined tolerance value.