3D textile reconstruction based on KinectFusion and synthesized texture. Issue 6 (6th November 2017)

• Record Type: Journal Article
• Authors: Hu, PengPeng; Komura, Taku; Li, Duan; Wu, Ge; Zhong, Yueqi
• Is Part Of: International journal of clothing science and technology. Volume 29:Issue 6(2017)
• Page Start: 793
• Page End: 806
• Publication Date: 2017-11-06
• Subjects: 3D scanning -- Convolutional neural networks -- KinectFusion -- Textile texture; Clothing and dress -- Periodicals; Textile fabrics -- Periodicals; 677
• DOI: 10.1108/IJCST-01-2017-0007
• Languages: English
• ISSNs: 0955-6222

Abstract

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.