A scaled multigrid optical flow algorithm based on the least RMS error between real and estimated second images
A scaled multigrid optical flow algorithm based on the least RMS error between real and estimated second images
复制标题
基于真实和估计第二图像之间最小均方根误差的缩放多重网格光流算法
DOI：
10.1016/s0031-3203(98)00105-8
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
S. Tamura
中科院分区：
文献类型：
--
作者：
M. Mahzoun;Jinwoo Kim;Satoru Sawazaki;K. Okazaki;S. Tamura
对于连续和均匀运动，我们设计了一种比例多重网格算法，其中水平的初始流量是由最优比例流量和误差流量之和计算的。最优缩放流是上一级的缩放扩展流，其可以生成相对于原始第二图像具有最小均方根误差的估计第二图像，并且误差流是(由最优缩放流生成的)估计第二图像和原始第二图像之间的流。然后使用原始的第一和第二图像以及该级别的初始流量来估计该级别的流量。从多重网格算法的各种最粗起始级别中，我们选择最终给出最佳估计流量的级别。
For continuous and uniform motions we have devised a scaled multigrid algorithm in which the initial flow for a level is calculated by the summation of the optimally scaled flow and the error flow. The optimally scaled flow is the scaled expanded flow of the previous level, which can generate an estimated second image having the least RMS error with respect to the original second image, and the error flow is the flow between the estimated second image (generated by the optimally scaled flow) and the original second image. The flow for this level is then estimated using the original first and second images and the initial flow for that level. From among the various coarsest starting levels of the multigrid algorithm, we select the one that finally gives the best-estimated flow.