GPU Accelerated Computation of Geometric Descriptors in Parametric Space

  • Anthousis AndreadisEmail author
  • Georgios Papaioannou
  • Pavlos MavridisEmail author
Part of the Communications in Computer and Information Science book series (CCIS, volume 598)


We present a novel generic method for the fast and accurate computation of geometric descriptors. While most existing approaches perform the computations directly on the geometric representation of the model, our method operates in parametric space, decoupling the computational complexity from the underlying mesh geometry. In contrast to other parametric space approaches, our method is not restricted to specific descriptors or parameterisations of the surface. By using the parametric space representation of the mesh geometry, we can trivially exploit massive parallel GPU architectures and achieve interactive computation times, while maintaining high accuracy. This renders the method suitable for computations involving large areas of support and animated shapes.


Geometric descriptors Parametric space Mesh geometry GPU acceleration 



This work was supported by EC FP7 STREP Project PRESIOUS, grant no. 600533. Armadillo, Lucy, Bunny and XYZ RGB Dragon models are from Stanford 3D Scanning Repository. Angel model is from the Large Geometric Models Archive of Georgia Institute of Technology. Rim model is from TurboSquid. All other models used are from the PRESIOUS project data collection.


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© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of InformaticsAthens University of Economics and BusinessAthensGreece

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