Video stitching based on multi-view spatiotemporal feature points and grid-based matching

Video stitching enables creation of videos with a wide field of view from videos captured from ordinary, probably moderately displaced, cameras. In this paper, a novel video stitching algorithm based on multi-view feature detection and registration using region-based statistics has been proposed. While stitching the videos captured using moving cameras, the motion in those cameras will affect the alignment of video frames. Movements in the cameras and in the objects will affect the temporal consistency while stitching the videos. Temporally reliable feature points are considered to maintain both spatial and temporal consistency using multi-view spatiotemporal feature points in this paper. Experiments have been carried out on different data sets, and the results showed the better and effective performance of the proposed approach.