Photometric Stereo with Non-Parametric and Spatially-Varying Reflectance
Kriegman, DavidNote: Order does not necessarily reflect citation order of authors.
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CitationAlldrin, Neil, Todd Zickler, and David Kreigman. Photometric stereo with non-parametric and spatially-varying reflectance. 2008. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, June 23-28. http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4587656
AbstractWe present a method for simultaneously recovering shape and spatially varying reflectance of a surface from photometric stereo images. The distinguishing feature of our approach is its generality; it does not rely on a specific parametric reflectance model and is therefore purely ldquodata-drivenrdquo. This is achieved by employing novel bi-variate approximations of isotropic reflectance functions. By combining this new approximation with recent developments in photometric stereo, we are able to simultaneously estimate an independent surface normal at each point, a global set of non-parametric ldquobasis materialrdquo BRDFs, and per-point material weights. Our experimental results validate the approach and demonstrate the utility of bi-variate reflectance functions for general non-parametric appearance capture.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:2894780
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