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.