gridfit

MATLAB Central File Exchange 8998. Surface Fitting using gridfit. Model 2-d surfaces from scattered data. Those wishing to model a surface from data in the form of z(x,y) from scattered or semi-scattered data have had few options in matlab - mainly griddata. Griddata is a valuable tool for interpolation of scattered data. However it fails when there are replicates or when the data has many collinear points. Griddata is also unable to extrapolate beyond the convex hull of the data unless the ’v4’ option is used, which is slow. Gridfit solves all of these problems, although it is not an interpolant. It builds a surface over a complete lattice, extrapolating smoothly into the corners. You have control of the amount of smoothing done, as well as interpolation methods, which solver to use, etc. This release allows the user to solve much larger problems using a new tiling option. There is essentially no limit on the size of the suface one builds now, as long as you have dense enough data and enough memory to store the final gridded surface.


References in zbMATH (referenced in 6 articles )

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  1. Zhang, Li; Balasuriya, Sanjeeva: Controlling trajectories globally via spatiotemporal finite-time optimal control (2020)
  2. Tombari, Federico; Salti, Samuele; Di Stefano, Luigi: Performance evaluation of 3D keypoint detectors (2013) ioport
  3. Islam, Syed M. S.; Davies, Rowan; Bennamoun, Mohammed; Mian, Ajmal S.: Efficient detection and recognition of 3D ears (2011) ioport
  4. Mian, A.; Bennamoun, M.; Owens, R.: On the repeatability and quality of keypoints for local feature-based 3D object retrieval from cluttered scenes (2010) ioport
  5. Smith, William A. P.; Hancock, Edwin R.: Estimating facial reflectance properties using shape-from-shading (2010) ioport
  6. Mian, Ajmal S.; Bennamoun, Mohammed; Owens, Robyn: Keypoint detection and local feature matching for textured 3D face recognition (2008) ioport