Range image segmentation by controlled-continuity spline approximation for parallel computation

Gilbert Maitre; Heinz Huegli

doi:10.1117/12.135148

1 February 1992 Range image segmentation by controlled-continuity spline approximation for parallel computation

Gilbert Maitre, Heinz Huegli

Proceedings Volume 1610, Curves and Surfaces in Computer Vision and Graphics II; (1992) https://doi.org/10.1117/12.135148
Event: Robotics '91, 1991, Boston, MA, United States

Abstract

A classical approach formulates surface reconstruction in terms of a variational problem by using two-dimensional surfaces defined by generalized spline functions. We present such an approach in the case of range image segmentation. The distinction of our approach lies in the way the discontinuities are detected. The spline is constrained to stay within a certain maximal distance to the discrete measured data, but is free as long as the maximum distance is not reached. Discontinuity emerges on points where the maximum distance constrains the spline. This method leads to a relaxation algorithm that solves the segmentation iteratively, by locally applying a relation that is close to the diffusion equation in the case of the membrane spline. Being iterative and local, the algorithm is suited for parallelism. We applied the method to range data from laser scanners using two different surface models: the membrane spline (more adequate for polyhedric objects), and the thin plate spline (more adequate for curved objects). The results illustrate the practical performance of this method which is simple, parallel, and controlled by few parameters.

Citation Download Citation

Gilbert Maitre and Heinz Huegli "Range image segmentation by controlled-continuity spline approximation for parallel computation", Proc. SPIE 1610, Curves and Surfaces in Computer Vision and Graphics II, (1 February 1992); https://doi.org/10.1117/12.135148

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