Illumination Robust Optical Flow Model Based on Histogram of Oriented Gradients

被引:0
|
作者
Rashwan, Hatem A. [1 ]
Mohamed, Mahmoud A. [2 ]
Garcia, Miguel Angel [3 ]
Mertsching, Baerbel [2 ]
Puig, Domenec [1 ]
机构
[1] Univ Rovira & Virgili, Tarragona, Spain
[2] Univ Paderborn, Get Lab, Paderborn, Germany
[3] Autonomous Univ Madrid, Madrid, Spain
来源
关键词
MOTION ESTIMATION; ACCURACY;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The brightness constancy assumption has widely been used in variational optical flow approaches as their basic foundation. Unfortunately, this assumption does not hold when illumination changes or for objects that move into a part of the scene with different brightness conditions. This paper proposes a variation of the L1-norm dual total variational (TV-L1) optical flow model with a new illumination-robust data term defined from the histogram of oriented gradients computed from two consecutive frames. In addition, a weighted non-local term is utilized for denoising the resulting flow field. Experiments with complex textured images belonging to different scenarios show results comparable to state-of-the-art optical flow models, although being significantly more robust to illumination changes.
引用
收藏
页码:354 / 363
页数:10
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