Entire shape scan system with multiple pro-cams using texture information and accurate silhouette creating technique

Yoshinori Oki, Marco Visentini-Scarzanella, Tomohito Wada, Ryo Furukawa, Ryusuke Sagawa, Hiroshi Kawasaki

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

1 Citation (Scopus)

Abstract

Recently, many approaches have been proposed for complete 3D reconstruction of moving objects. Particularly, one-shot reconstruction using a projector-camera system (pro-cam) has attracted considerable attention as it can reconstruct the full 3D shape from a single image and it is therefore suitable for capturing moving objects. However, one-shot measurement methods have the issue that the projection pattern is easily affected by the texture of the target object and its background. Furthermore, background subtraction can be inaccurate due to the shadow cast by the target object. In this paper, we propose a method to solve these issues using texture estimation and online background synthesis techniques, by relying on a dictionary of pre-captured images. By applying these methods to our multi-view pro-cams, we can demonstrate the robustness of our approach for one-shot reconstruction of moving objects, with reduced sensitivity to texture and cast shadows.

Original languageEnglish
Title of host publicationProceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages18-21
Number of pages4
ISBN (Electronic)9784901122153
DOIs
Publication statusPublished - Jul 8 2015
Externally publishedYes
Event14th IAPR International Conference on Machine Vision Applications, MVA 2015 - Tokyo, Japan
Duration: May 18 2015May 22 2015

Publication series

NameProceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015

Other

Other14th IAPR International Conference on Machine Vision Applications, MVA 2015
CountryJapan
CityTokyo
Period5/18/155/22/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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