Building Volumetric Appearance Models of Fabric Using Micro CT Imaging.
Cloth is essential to our everyday lives; consequently, visualizing and rendering cloth has been an important area of research in graphics for decades. One important aspect contributing to the rich appearance of cloth is its complex 3D structure. Volumetric algorithms that model this 3D structure ca...
| Publicado en: | Communications of the ACM Vol. 57; no. 11; pp. 98 - 106 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Association for Computing Machinery
Nov2014
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=99078948&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 99078948 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Nov2014 vid: 57 iid: 11 pid: 68 pub: Association for Computing Machinery artinfo: ui: 99078948 10.1145/2670517 ppf: 98 ppct: 8 formats: tig: atl: Building Volumetric Appearance Models of Fabric Using Micro CT Imaging. aug: au: Shuang Zhao Jakob, Wenzel Marschner, Steve Bala, Kavita affil: Cornell University, Ithaca, NY su: Textiles Algorithm research Computer graphics research Computed tomography Computer science research Three-dimensional textiles sug: subj: Textiles Algorithm research Computer graphics research Computed tomography Computer science research Three-dimensional textiles ab: Cloth is essential to our everyday lives; consequently, visualizing and rendering cloth has been an important area of research in graphics for decades. One important aspect contributing to the rich appearance of cloth is its complex 3D structure. Volumetric algorithms that model this 3D structure can correctly simulate the interaction of light with cloth to produce highly realistic images of cloth. But creating volumetric models of cloth is difficult: writing specialized procedures for each type of material is onerous, and requires significant programmer effort and intuition. Further, the resulting models look unrealistically “perfect” because they lack visually important features like naturally occurring irregularities. This paper proposes a new approach to acquiring volume models, based on density data from X-ray computed tomography (CT) scans and appearance data from photographs under uncontrolled illumination. To model a material, a CT scan is made, yielding a scalar density volume. This 3D data has micron resolution details about the structure of cloth but lacks all optical information. So we combine this density data with a reference photograph of the cloth sample to infer its optical properties. We show that this approach can easily produce volume appearance models with extreme detail, and at larger scales the distinctive textures and highlights of a range of very different fabrics such as satin and velvet emerge automatically—all based simply on having accurate mesoscale geometry. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2014 holdings: @attributes: islocal: N |
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