Abstract:

Complex reflectance phenomena such as specular reflections confound many vision problems since they produce image `features' that do not correspond directly to intrinsic surface properties such as shape and spectral reflectance. A common approach to mitigate these effects is to explore functions of an image that are invariant to these photometric events. In this paper we describe two such invariants--one invariant to specular reflections, and the other invariant to both specular reflections and diffuse shading--that result from exploiting color information in images of dichromatic surfaces. These invariants are derived from subspaces of RGB color space, and they enable the application of Lambertian-based vision techniques to a broad class of specular, non-Lambertian scenes. Using implementations of recent algorithms taken from the literature, we demonstrate the practical utility of these invariants for a wide variety of applications, including stereo, shape from shading, material-based segmentation, and motion estimation.

References:

• Todd Zickler, Satya P. Mallick, David J. Kriegman, and Peter N. Belhumeur, "Color Subspaces as Photometric Invariants." Accepted for publication in International Journal of Computer Vision. [PDF][SpringerLink]

• Todd Zickler, Satya P. Mallick, David J. Kriegman, and Peter N. Belhumeur, "Color Subspaces as Photometric Invariants." Proc. IEEE Conference on Computer Vision and Pattern Recognition, June 2006. [PDF][IEEE Xplore]

• Satya P. Mallick, Todd Zickler, David J. Kriegman, and Peter N. Belhumeur, "Beyond Lambert: Reconstructing Specular Surfaces Using Color." Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2005. [PDF] [IEEE Xplore]

Some of this material is based upon work supported by the National Science Foundation under Grant No. 0541173. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Updated: Jan 3, 2008