Reconstructing Objects with Real-World Materials

Photometric and Multiview Stereo Methods

Objects with complex reflectance (shiny objects) are difficult to obtain using geometric shape reconstruction methods like laser scanners. However, photographing a surface under multiple lighting conditions can make it possible to distinguish different normals and different materials on the surface. The following projects exploit this photometric sampling approach to recover models of shape and reflectance in such challenging cases.

In the first two projects, we use a reference object with known shape to match up pixels with their correct normals. In the third project we show that the reference objects can be replaced with parametric models.

Shape and Materials By Example

Aaron Hertzmann, Steven M. Seitz. Example-Based Photometric Stereo: Shape Reconstruction with General, Varying BRDFs. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 8, pp. 1254-1264, August 2005. [PDF]

Aaron Hertzmann, Steven M. Seitz. Shape and Materials by Example: A Photometric Stereo Approach. Proc. IEEE CVPR 2003. Madison, WI. June 2003. Vol. 1. pp. 533-540. [PDF] (Earlier conference version of previous paper)

Example-Based Stereo with General BRDFs

Adrien Treuille, Aaron Hertzmann, Steven M. Seitz. Example-Based Stereo with General BRDFs. 8th European Conference on Computer Vision (ECCV 2004). Prague, Czech Republic, May 2004. [PDF]

Shape and Spatially-Varying BRDFs from Photometric Stereo

Dan B Goldman, Brian Curless, Aaron Hertzmann and Steven M. Seitz. Shape and Spatially-Varying BRDFs From Photometric Stereo, in Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV 2005), Beijing, China, October 2005. [PDF]

Dan B Goldman, Brian Curless, Aaron Hertzmann and Steven M. Seitz. Shape and Spatially-Varying BRDFs From Photometric Stereo. UW CSE Technical Report 04-05-03, 2004. [PDF] (Earlier technical report version of previous paper)

Project Members