Stereo Based Computational Photography


Abstract
        The ability to produce dynamic Depth of Field effects in live video streams was until recently a quality unique to movie cameras. In this paper, we present a computational camera solution coupled with real-time GPU processing to produce runtime dynamic Depth of Field effects. We first construct a hybrid-resolution stereo camera with a high-res/low-res camera pair. We recover a low-res disparity map of the scene using GPU-based Belief Propagation and subsequently upsample it via fast Cross/Joint Bilateral Upsampling. With the recovered high-resolution disparity map, we warp the high-resolution video stream to nearby viewpoints to synthesize a light field towards the scene. We exploit parallel processing and atomic operations on the GPU to resolve visibility when multiple pixels warp to the same image location.

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