Efficient and Prioritized Point Subsampling for CSRBF Compression

  title={Efficient and Prioritized Point Subsampling for CSRBF Compression},
  author={Masaki Kitago and Meenakshisundaram Gopi},
We present a novel cost function to prioritize points and subsample a point set based on the dominant geometric features and local sampling density of the model. This cost function is easy to compute and at the same time provides rich feedback in the form of redundancy and non-uniformity in the sampling. We use this cost function to simplify the given point set and thus reduce the CSRBF (Compactly Supported Radial Basis Function) coefficients of the surface fit over this point set. Further… CONTINUE READING


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