The computational power of GPU-based algorithms is receiving increased attention in research on Computer Vision and 3D stereo reconstruction from images. In this context one of the most important ingredients for any 3D stereo reconstruction technique is the estimation of photo-consistency. This ECCV06 paper presents a new, illumination invariant photo-consistency measure for high quality, volumetric 3D reconstruction from calibrated images. In contrast to current standard methods such as normalized cross-correlation it supports unconstrained camera setups and non-planar surface approximations. The paper shows how this measure as well as the other important stages of the volumetric reconstruction pipeline can be implemented in a highly efficient way by exploiting current graphics processors. The authors' GPU implementation achieves speedups up to a factor of 85 in comparison to CPU-based algorithms, and allows reconstruction of high quality models with computation times of only a few seconds to minutes, even for large numbers of cameras and high volumetric resolutions. ( Robust and Efficient Photo-Consistency Estimation for Volumetric 3D Reconstruction. Alexander Hornung and Leif Kobbelt. European Conference on Computer Vision (ECCV 2006), LNCS, vol. 3952, Springer, 179-190.)