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Starting with a 2D grid of registered videos acquired on a robotic mount, we formulate a combinatorial optimization to determine for each output pixel the source video and looping parameters that jointly maximize spatiotemporal consistency. This optimization is accelerated by reducing the set of source labels using a graph-coloring scheme. We parallelize the computation and implement it out-of-core by partitioning the domain along low-importance paths. The merged panorama is assembled using gradient-domain blending and stored as a hierarchy of video tiles. Finally, an interactive viewer adaptively preloads these tiles for responsive browsing and allows the user to interactively edit and improve local regions. 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