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 language | English |
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Pages (from-to) | 355-364 |
Number of pages | 10 |
Journal | Procedia Computer Science |
Volume | 108 |
Early online date | 9 Jun 2017 |
DOIs | |
Publication status | Published - 14 Jun 2017 |
Keywords / Materials (for Non-textual outputs)
- Textile texture
- 3D scanning
- Convolutional neural networks