A triangle mesh reconstruction method taking into account silhouette images

Michihiro Mikamo, Yoshinori Oki, Marco Visentini-Scarzanella, Hiroshi Kawasaki, Ryo Furukawa, Ryusuke Sagawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we propose a novel approach to reconstruct triangle meshes from point sets by taking the silhouette of the target object into consideration. Recently, many approaches have been proposed for complete 3D reconstruction of moving objects. For example, motion capture techniques are used to acquire 3D data of human motion. However, it needs to attach markers onto the joints, which results in limiting the capturing environments and the number of data that can be acquired. In contrast, to obtain dense data of 3D object, multi-view stereo scanning system is one of the powerful methods. It utilize images taken by several directions and enables to reconstruct 3D dense point sets by using Epipolar geometry. However, it is still challenging problem to reconstruct 3D triangle mesh from the 3D point sets due to the abundant points originated by mismatched points between images. We propose a novel approach to obtain more accurate triangle mesh reconstruction method than the previous one. We take advantage of silhouette images acquired in the process of reconstructing 3D point sets that result in removing noises and compensating holes. Finally, we demonstrate that the proposed method can generate the details of the surface, where the previous method loses from a small number of points.

Original languageEnglish
Title of host publicationImage and Video Technology - 7th Pacific-Rim Symposium, PSIVT 2015, Revised Selected Papers
EditorsMariano Rivera, Brendan McCane, Xinguo Yu, Thomas Bräunl
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319294506
Publication statusPublished - 2016
Externally publishedYes
Event7th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2015 - Auckland, New Zealand
Duration: Nov 25 2015Nov 27 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other7th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2015
Country/TerritoryNew Zealand

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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