A fast T-spline fitting method based on efficient region segmentation

Abstract

T-spline has been recently developed to represent objects of arbitrary shapes in computer-aided design, computer graphics, and reverse engineering. In fact, fitting a T-spline over a point cloud is usually ineffective by using traditional iterative fit-and-refine paradigm. In traditional T-spline least-square fitting method, all control points are recomputed in each iteration, which costs large amount of calculations. In this paper, we propose a fast T-spline fitting method based on T-mesh segmentation. The segmentation technology is introduced to identify the inactive and active region of T-mesh. Computational costs can be largely reduced since only the control points in the active part need to be recalculated in the upcoming process, while those in inactive part are kept invariant once the fitting accuracy is achieved. Classical datasets are used to validate the proposed fast fitting method, and the experimental results yield that a total running time is reduced to $$34\%$$ of the traditional T-spline fitting method. We argue this method is particularly useful in the reconstruction of scanned scatter data of which the parameter distribution is not uniform.