光流
计算机科学
估计
流量(数学)
计算机视觉
人工智能
光学成像
算法
图像(数学)
数学
光学
物理
工程类
几何学
系统工程
作者
Rui Zhao,Ruiqin Xiong,Shuyuan Zhu,Bing Zeng,Tiejun Huang,Wen Gao
标识
DOI:10.1109/vcip49819.2020.9301771
摘要
Traditional optical flow estimation methods mostly focus on images of the same resolution. However, there are some situations requiring optical flow between images of different resolutions, where the traditional approaches suffer from the inequality of spectrum aliasing level. In this paper, we propose a method estimating the flow fields between a clear image and a highly undersampled one. The proposed method simultaneously describes the motion and integral relationship between the images via an integral form image under the assumption of brightness and gradient consistency as well as motion smoothness. We also derive the numerical solution briefly, through which we can solve the equations easily via linearizations. Experimental results on Middlebury and MPI-Sintel datasets demonstrate that our proposed method outperforms traditional methods preprocessing images of different resolutions to be the same size, offering more accurate results.
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