We present a light field synthesis technique that achieves accurate reconstruction given a low-cost, wide-baseline camera rig. Our system integrates optical flow with methods for rectification, disparity estimation, and feature extraction, which we then feed to a neural network view synthesis solver with wide-baseline capability. We propose two novel warping methods that improve the accuracy of disparity estimation and view synthesis. The methods enable the use of off-the-shelf surveillance camera hardware in a simplified and expedited capture workflow. A thorough analysis of the process and resulting view synthesis accuracy over state of the art is provided.
Martin Jaggi, Vinitra Swamy, Jibril Albachir Frej, Julian Thomas Blackwell
Friedrich Eisenbrand, Puck Elisabeth van Gerwen, Raimon Fabregat I De Aguilar-Amat
Martin Vetterli, Eric Bezzam, Matthieu Martin Jean-André Simeoni