Evangelos Kalogerakis, Derek Nowrouzezahrai, Patricio Simari, Karan Singh, "Extracting lines of curvature from noisy point clouds" , Special Issue of the Computer-Aided Design journal on Point-Based Computational Techniques, Volume 41, Number 4 (April 2009), pp. 282-292


We present a robust framework for extracting lines of curvature from point clouds. First, we show a novel approach to denoising the input point cloud using robust statistical estimates of surface normal and curvature which automatically rejects outliers and corrects points by energy minimization. Then the lines of curvature are constructed on the point cloud with controllable density. Our approach is applicable to surfaces of arbitrary genus, with or without boundaries, and is statistically robust to noise and outliers while preserving sharp surface features. We show our approach to be e ective over a range of synthetic and real-world input datasets with varying amounts of noise and outliers. The extraction of curvature information can bene fit many applications in CAD, computer vision and graphics for point cloud shape analysis, recognition and segmentation. Here, we show the possibility of using the lines of curvature for feature-preserving mesh construction directly from noisy point clouds.

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  Author    = {Evangelos Kalogerakis and Derek Nowrouzezahrai and Patricio Simari and Karan Singh},
  Title     = {Extracting lines of curvature from noisy point clouds},
  Journal   = {Special Issue of the {E}lsevier {C}omputer-{A}ided {D}esign journal on {P}oint-{B}ased {C}omputational {T}echniques},
  Volume    = {41},
  Number    = {4},
  Pages     = {282--292},
  Year      = {2009},