A Simple and Effective Fusion Approach for Multi-frame Optical Flow Estimation

被引:0
|
作者
Ren, Zhile [1 ]
Gallo, Orazio [2 ]
Sun, Deqing [2 ]
Yang, Ming-Hsuan [3 ]
Sudderth, Erik B. [4 ]
Kautz, Jan [2 ]
机构
[1] Brown Univ, Providence, RI 02912 USA
[2] NVIDIA, Santa Clara, CA 95051 USA
[3] UC Merced, Merced, CA USA
[4] UC Irvine, Irvine, CA USA
关键词
Multi-frame optical flow; Temporal optical flow fusion;
D O I
10.1007/978-3-030-11024-6_53
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To date, top-performing optical flow estimation methods only take pairs of consecutive frames into account. While elegant and appealing, the idea of using more than two frames has not yet produced state-of-the-art results. We present a simple, yet effective fusion approach for multi-frame optical flow that benefits from longer-term temporal cues. Our method first warps the optical flow from previous frames to the current, thereby yielding multiple plausible estimates. It then fuses the complementary information carried by these estimates into a new optical flow field. At the time of writing, our method ranks first among published results in the MPI Sintel and KITTI 2015 benchmarks.
引用
收藏
页码:706 / 710
页数:5
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