Non-rigid surface tracking for virtual fitting system

Naoki Shimizu, Takumi Yoshida, Tomoki Hayashi, Francois De Sorbier, Hideo Saito

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

3 Citations (Scopus)

Abstract

In this paper, we describe a method for overlaying a texture onto a T-shirt, for improving current virtual fitting system. In such systems, users can try on clothes virtually. In order to realize such a system, a depth camera has been used. These depth cameras can capture 3D data in real time and have been used by some industrial virtual cloth fitting systems. However, these systems roughly, or just do not, consider the shape of the clothes that user is wearing. So the appearance of these virtual fitting systems looks unnaturally. For a better fitting, we need to estimate 3D shape of cloth surface, and overlay a texture of the cloth that the user wants to see onto the surface. There are some methods that register a 3D deformable mesh onto captured depth data of a target surface. Although those registration methods are very accurate, most of them require large amount of processing time or either manually-set markers or special rectangles. The main contribution of our method is to overlay a texture onto a texture of T-shirt in real-time without modifying the surface.

Original languageEnglish
Title of host publicationVISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
Pages12-18
Number of pages7
Publication statusPublished - 2013 May 31
Event8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 - Barcelona, Spain
Duration: 2013 Feb 212013 Feb 24

Publication series

NameVISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
Volume2

Other

Other8th International Conference on Computer Vision Theory and Applications, VISAPP 2013
Country/TerritorySpain
CityBarcelona
Period13/2/2113/2/24

Keywords

  • Augmented reality
  • Deformable 3D registration
  • Local feature point
  • Principal component analysis
  • RGB-D camera

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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