A novel video stitching algorithm is proposed which stitches video streams captured by multi-UAVs into panorama video streams. Each UAV captures one video streams, there are independent shakiness and parallax between each temporally aligned frames. A pure 2D homography does not have the capability to solve parallax like spatial-variant homographies, where each input video frame is sliced into grids and each grid is transformed with a local 2D homography. Video stitching has to consider video stabilization due to strong temporal correlations between frames. Video stitching and stabilization are combined, since they are both about putting the grids from video sources into panorama properly. Good stitching results are generated by optimizing the camera paths which describe the grid transformation between girds of frames before and after. In 4 aspects they are optimized: 1) spatially with the grids around, 2) temporally with the grid at the same place from before and after frames, 3) geometrically with the grids from another video, 4) reliably not too far from the original transformations. We focus on video stream processing which does not need the whole video frames, only 7 frames later than the input, state-of-the-art results are generated.
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