de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Image-Based Reconstruction of Spatially Varying Materials

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44911

Lensch,  Hendrik P. A.
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44747

Kautz,  Jan
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44506

Goesele,  Michael
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44602

Heidrich,  Wolfgang
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Lensch, H. P. A., Kautz, J., Goesele, M., Heidrich, W., & Seidel, H.-P. (2001). Image-Based Reconstruction of Spatially Varying Materials. In S. Gortler, & K. Myszkowski (Eds.), Rendering Techniques 2001: Proceedings of the 12th Eurographics Workshop on Rendering (pp. 104-115). Vienna, Austria: Springer.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-32A1-7
Abstract
The measurement of accurate material properties is an important step towards photorealistic rendering. Many real-world objects are composed of a number of materials that often show subtle changes even within a single material. Thus, for photorealistic rendering both the general surface properties as well as the spatially varying effects of the object are needed. We present an image-based measuring method that robustly detects the different materials of real objects and fits an average bidirectional reflectance distribution function (BRDF) to each of them. In order to model the local changes as well, we project the measured data for each surface point into a basis formed by the recovered BRDFs leading to a truly spatially varying BRDF representation. A high quality model of a real object can be generated with relatively few input data. The generated model allows for rendering under arbitrary viewing and lighting conditions and realistically reproduces the appearance of the original object.