3D High-quality Textile Reconstruction with Synthesized Texture

Abstract 3D garment model plays an important role in the fashion industry. However, not much work focus on extracting high-quality clothes from scanned data. The texture is limited by photography methods in 3D scanning. This paper proposes a novel framework of reconstructing high-quality 3D garment models with synthesized texture. Firstly, a pipeline of 3D garment processing is proposed to obtain a better 3D model based on KinectFusion. Then, DeepTextures is used to synthesize a new texture. To our best knowledge, this is the first paper combining 3D garment reconstruction and texture synthesis. Experimental results show that our method can conveniently obtain 3D garment models and realistic textures.

[1]  Leon A. Gatys,et al.  Texture Synthesis Using Convolutional Neural Networks , 2015, NIPS.

[2]  Frédo Durand,et al.  Non-iterative, feature-preserving mesh smoothing , 2003, ACM Trans. Graph..

[3]  Stefan B. Williams,et al.  Linear Volumetric Focus for Light Field Cameras , 2015, TOGS.

[4]  Eero P. Simoncelli,et al.  A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients , 2000, International Journal of Computer Vision.

[5]  Andrew W. Fitzgibbon,et al.  KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera , 2011, UIST.

[6]  Wei Zhao,et al.  A Robust Hole-Filling Algorithm for Triangular Mesh , 2007, CAD/Graphics.

[7]  Trevor Darrell,et al.  Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.

[8]  Ferdinand Fuhrmann,et al.  EVALUATION OF THE SPATIAL RESOLUTION ACCURACY OF THE FACE TRACKING SYSTEM FOR KINECT FOR WINDOWS V 1 AND V 2 , 2014 .

[9]  Andrea Fossati,et al.  Consumer Depth Cameras for Computer Vision , 2013, Advances in Computer Vision and Pattern Recognition.

[10]  Thomas Butkiewicz.  Low-cost coastal mapping using Kinect v2 time-of-flight cameras , 2014, 2014 Oceans - St. John's.

[11]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[12]  Olga Sorkine-Hornung,et al.  Instant field-aligned meshes , 2015, ACM Trans. Graph..

[13]  Matthew Q. Hill,et al.  Body talk , 2016, ACM Trans. Graph..

[14]  Tomás Pajdla,et al.  3D with Kinect , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[15]  Xiaoou Tang,et al.  Learning a Deep Convolutional Network for Image Super-Resolution , 2014, ECCV.

[16]  Jorge Nocedal,et al.  Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization , 1997, TOMS.

[17]  Daniel Cohen-Or,et al.  Bilateral mesh denoising , 2003 .

[18]  Greg Humphreys,et al.  A spatial data structure for fast Poisson-disk sample generation , 2006, SIGGRAPH 2006.