Joint planar parameterization of segmented parts and cage deformation for dense correspondence Srinivasan Ramachandran, Donya Ghafourzadeh, Martin de Lasa, Tiberiu Popa, and Eric Paquette Computers & Graphics, Volume 74, pp. 202-212, 2018. Presented at the Shape Modeling International (SMI) 2018 Conference, Lisbon, Portugal, June 6-8, 2018

Abstract

In this paper, we present a robust and efficient approach for computing a dense registration between two surface meshes. The proposed approach exploits a user-provided sparse set of landmarks, positioned at semantic locations, along with closed paths connecting sequences of landmarks. The approach segments the mesh and then flattens the segmented parts using angle-based flattening and low distortion boundary constraints. It adjusts the segmented parts with a cage deformation to align the interior landmarks. As a last step, our approach extracts the dense registration from the flattened and deformed segmented parts. The approach is capable of handling a wide range of surfaces, and is not limited to genus-zero surfaces. It handles small features, such as fingers and facial attributes, as well as non-isometric pairs and pairs in different poses. The results show that the proposed approach is superior to current state-of-the-art methods.

Keywords

BibTeX entry

@Article{Ramachandran:2018:CG,
  author =       "Srinivasan Ramachandran and Donya Ghafourzadeh and Martin de Lasa and Tiberiu Popa and Eric Paquette",
  title =        "Joint planar parameterization of segmented parts and cage deformation for dense correspondence",
  journal = {Computers \& Graphics},
  publisher = {Elsevier},  
  volume = {74},
  pages = {202-212},
  year = {2018},
}

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