View-graph is an essential input to large-scale structure from motion (SfM) pipelines. Accuracy and efficiency of large-scale SfM is crucially dependent on the input view-graph. Inconsistent or inaccurate edges can lead to inferior or wrong reconstruction. Most SfM methods remove `undesirable' images and pairs using several fixed heuristic criteria, and propose tailor-made solutions to achieve specific reconstruction objectives such as efficiency, accuracy, or disambiguation.
Replacing overexposed or dull skies in outdoor photographs is a desirable photo manipulation. It is often necessary to color correct the foreground after replacement to make it consistent with the new sky. Methods have been proposed to automate the process of sky replacement and color correction. However, many times a color correction is unwanted by the artist or may produce unrealistic results.
Progress in the field of 3D Computer Vision has led to the development of robust SfM (Structure from Motion) algorithms. These SfM algorithms, allow us to build 3D models of the monuments using community photo collections. We work on improving the speed and accuracy of these SfM algorithms and also on developing tools that use the rich geometry present in the SfM datasets.