9 April 2018 An improved multi-paths optimization method for video stabilization
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Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 106090N (2018) https://doi.org/10.1117/12.2284442
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
For video stabilization, the difference between original camera motion path and the optimized one is proportional to the cropping ratio and warping ratio. A good optimized path should preserve the moving tendency of the original one meanwhile the cropping ratio and warping ratio of each frame should be kept in a proper range. In this paper we use an improved warping-based motion representation model, and propose a gauss-based multi-paths optimization method to get a smoothing path and obtain a stabilized video. The proposed video stabilization method consists of two parts: camera motion path estimation and path smoothing. We estimate the perspective transform of adjacent frames according to warping-based motion representation model. It works well on some challenging videos where most previous 2D methods or 3D methods fail for lacking of long features trajectories. The multi-paths optimization method can deal well with parallax, as we calculate the space-time correlation of the adjacent grid, and then a kernel of gauss is used to weigh the motion of adjacent grid. Then the multi-paths are smoothed while minimize the crop ratio and the distortion. We test our method on a large variety of consumer videos, which have casual jitter and parallax, and achieve good results.
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Tao Qin, Tao Qin, Sheng Zhong, Sheng Zhong, } "An improved multi-paths optimization method for video stabilization", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106090N (9 April 2018); doi: 10.1117/12.2284442; https://doi.org/10.1117/12.2284442


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