3D High-quality Textile Reconstruction with Synthesized Texture

Pengpeng Hu, Taku Komura, Duan Li, Ge Wu, Yueqi Zhong

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

3D textile model plays an important role in textile engineering. However, not much work focus on high-quality 3D textile reconstruction. The texture is also limited by photography methods in 3D scanning. This paper presents a novel framework of reconstructing a high-quality 3D textile model with a synthesized texture. Firstly, a pipeline of 3D textile processing is proposed to obtain a better 3D model based on KinectFusion. Then, convolutional neural networks (CNN) is used to synthesize a new texture. To our best knowledge, this is the first paper combining 3D textile reconstruction and texture synthesis. Experimental results show that our method can conveniently obtain high-quality 3D textile models and realistic textures.
Original languageEnglish
Pages (from-to)355-364
Number of pages10
JournalProcedia Computer Science
Volume108
Early online date9 Jun 2017
DOIs
Publication statusPublished - 14 Jun 2017

Keywords / Materials (for Non-textual outputs)

  • Textile texture
  • 3D scanning
  • Convolutional neural networks

Fingerprint

Dive into the research topics of '3D High-quality Textile Reconstruction with Synthesized Texture'. Together they form a unique fingerprint.

Cite this