3D textile reconstruction based on KinectFusion and synthesized texture

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

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Purpose
The purpose of this paper is to present a novel framework of reconstructing the 3D textile model with synthesized texture.

Design/methodology/approach
First, a pipeline of 3D textile reconstruction based on KinectFusion is proposed to obtain a better 3D model. Second, “DeepTextures” method is applied to generate new textures for various three-dimensional textile models.

Findings
Experimental results show that the proposed method can conveniently reconstruct a three-dimensional textile model with synthesized texture.

Originality/value
A novel pipeline is designed to obtain 3D high-quality textile models based on KinectFusion. The accuracy and robustness of KinectFusion are improved via a turntable. To the best of the authors’ knowledge, this is the first paper to explore the synthesized textile texture for the 3D textile model. This is not only simply mapping the texture onto the 3D model, but also exploring the application of artificial intelligence in the field of textile.
Original languageEnglish
Pages (from-to)793-806
Number of pages14
JournalInternational Journal of Clothing Science and Technology
Volume29
Issue number6
Early online date24 Nov 2017
DOIs
Publication statusPublished - 30 Nov 2017
Externally publishedYes

Keywords

  • 3D scanning
  • Convolution neural networks
  • KinectFusion
  • Textile texture

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