Stereo vision for 3D clothing image generation
This paper presents a newly developed stereo vision system for generating 3D images of gar-ments attired by a subject or or a mannequin. 3D clothing images provide more realistic and effective visualization for showing clothings style, drape, and fit than 2d images. The system consists of four i-dentical imaging units that can be reconfigured to cover the top, bottom or entire body. Each unit contains a pair of digital cameras and a projector. The cameras capture two images from different perspectives, and the projector Creates artificial textures onto the clothing surface that help to reduce stereo matching ambiguity. A two-phase algorithm was developed to permit sub-pixel, dense stereo matching, In the first phase, the foreground (garment) is segmented by using a predefined virtual interface in the disparity space image, and a coarse disparity map is generated with block matching. In the second phase, local least squares matching is performed along with global optimization within a regularization framework which ensures both accuracy and reliability of 3D data generation. The unorganized data clouds are the processed by a surface modeling algorithm, which is based on a triangular mesh, surface subdivision and optimization, to reconstruct smooth and complete a clothing surface.
garment stereo vision 3D image
XU Bu-gao YU Wu-rong
School of Human Ecology, University of Texas at Austin,Austin, TX 78712, USA
国际会议
2009 International Teztile Science and Technology Forum(2009国际纺织科学技术论坛)
西安
英文
431-436
2009-04-01（万方平台首次上网日期，不代表论文的发表时间）