Lighting transfer across multiple views through local color transforms

We present a method for transferring lighting across photographs of a static scene. Our method takes as input a photo collection depicting a scene under varying viewpoints and lighting conditions. We cast lighting transfer as a colorization problem, where the transfer of local illumination across images is guided by sparse correspondences obtained through multi-view stereo. Instead of directly propagating color, we learn local color transforms from corresponding patches in pairs of images and propagate these transforms in an edge-aware manner in regions with no correspondences. Our color transforms model the large variability of appearance changes in local regions of the scene, and are robust to missing or inaccurate correspondences. The method is fully automatic and is able to transfer strong shadows across images. We show applications of our image relighting method, for browsing collections of photographs with harmonized lighting and for generating synthetic timelapses.