FasTFit: A Fast T-spline Fitting Algorithm

    •  Feng, C., Taguchi, Y., "FasTFit: A Fast T-spline Fitting Algorithm", Computer-Aided Design, DOI: 10.1016/​j.cad.2017.07.002, Vol. 92, pp. 11-21, November 2017.
      BibTeX TR2017-141 PDF Video
      • @article{Feng2017nov,
      • author = {Feng, Chen and Taguchi, Yuichi},
      • title = {FasTFit: A Fast T-spline Fitting Algorithm},
      • journal = {Computer-Aided Design},
      • year = 2017,
      • volume = 92,
      • pages = {11--21},
      • month = nov,
      • doi = {10.1016/j.cad.2017.07.002},
      • url = {}
      • }
  • Research Area:

    Computer Vision


T-spline has been recently developed to represent objects of arbitrary shapes using a smaller number of control points than the conventional NURBS or B-spline representations in computer aided design, computer graphics, and reverse engineering. However, existing methods for fitting a T-spline over a point cloud are slow. By shifting away from the conventional iterative fitand-refine paradigm, we present a novel split-connect-fit algorithm to more efficiently perform the T-spline fitting. Through adaptively dividing a point cloud into a set of B-spline patches, we first discover a proper topology of T-spline control points, i.e., the T-mesh. We then connect these B-spline patches into a single T-spline surface with different continuity options between neighboring patches according to the data. The T-spline control points are initialized from their correspondences in the B-spline patches, which are refined by using a conjugate gradient method. In experiments using several types of large-sized point clouds, we demonstrate that our algorithm is at least an order of magnitude faster than state-of-the-art algorithms while provides comparable or better results in terms of quality and conciseness.


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