Smooth image surface approximation by piecewise cubic polynomials

  • Authors:
  • Oliver Matias Van Kaick;Helio Pedrini

  • Affiliations:
  • School of Computing Science, Simon Fraser University, Burnaby, BC, Canada;Department of Computer Science, Federal University of Paraná, Curitiba, PR, Brazil

  • Venue:
  • CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
  • Year:
  • 2007

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Abstract

The construction of surfaces from dense data points is an important problem encountered in several applications, such as computer vision, reverse engineering, computer graphics, terrain modeling, and robotics. Moreover, the particular problem of approximating digital images from a set of selected points allows to employ methods that are directed specifically to this task, which take advantage of the fact that all points belong to a common 2D domain. This paper describes a method for approximating images by fitting smooth surfaces to scattered points, where the smooth surfaces are constructed using piecewise cubic approximation. An incremental triangulation algorithm is used to iteratively refine a mesh until a specified error tolerance is achieved. The resulting surface is represented by a network of piecewise cubic triangular patches possessing C1 continuity. The proposed method is compared against other surface approximation approaches and applied to several data sets in order to demonstrate its performance.