一种基于线性亮度变化模型的鲁棒的光流算法

Robust estimation of optical flow based on linear brightness model

提出了一种鲁棒光流算法,用于计算光照强度、帧间运动速度及运动速度变化较大情况下的光流场。在梯度约束方程中嵌入了线性亮度变化模型,以提高大的光照强度变化下算法稳健性;将各向异性扩散方程引入空间方向平滑约束,以改善运动不连续处的流速计算精度,并依此建立了多尺度空间微分光流算法。参数的均衡化得到了线性尺度变化下的恒定能量函数。迭代运算引入运动补偿的概念,使亮度误差减小。实验结果表明,在光照强度和运动速度及速度变化较大时,本文算法具有很好的计算精度,并产生密度100%的光流场。

A robust optical flow algorithm for larger motion velocity and larger velocity change under large varying illumination was presented, A general linear brightness model was embedded in the gradient constraint equation, which improved algorithmic stability under large varying illumination, The anisotropic diffusion equation was introduced in the spatial oriented smoothness constraint, so that it can improve the computation of flow velocity in the motion discontinuities, according to these improvements, the differential optical flow algorithm based on multi-scale-space focusing was used. An invariant energy function under the linear variation of scales was obtained by normalizing the parameters. Motion compensation is introduced to iterative process, and then the error of brightness was decreased. The experimental results show that the algorithm proposed in this paper provides with good computation accuracy for lager motion velocity and larger velocity change, and the flow field of 100% density can be created.