Image mosaicing based on optical flow metric
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Video mosaicing has been viewed traditionally as problem of registering (and stitching) only successive video frames. While some of the recent global alignment approaches make use of the information stemming from non-consecutive pairs of video frames, the registration of each frame pair is typically done independently. No real emphasis has been laid on how the imaging process and the camera motion relate the pair-wise homographies. Therefore, accurate registration and in turn, mosaicing, especially, in face of poor feature point correspondence, still remains a challenging task. For example, mo...
Video mosaicing has been viewed traditionally as problem of registering (and stitching) only successive video frames. While some of the recent global alignment approaches make use of the information stemming from non-consecutive pairs of video frames, the registration of each frame pair is typically done independently. No real emphasis has been laid on how the imaging process and the camera motion relate the pair-wise homographies. Therefore, accurate registration and in turn, mosaicing, especially, in face of poor feature point correspondence, still remains a challenging task. For example, mosaicing a desert video wherein the frames have minimal texture to provide feature points (e.g. corners) or mosaicing in presence of repetitive texture leading to several mismatched points is highly error-prone.
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