图像光流联合驱动的变分光流计算新方法

New algorithm for estimation of variational optical flow with image-and flow-driven

提出一种基于图像光流联合驱动的变分光流计算方法。数据项采用灰度守恒和梯度守恒相结合、局部约束与全局约束结合的思想,并引入正则化因子提高计算精度。平滑项采用图像与光流联合驱动的各向异性平滑策略,将数据项与平滑项紧密地联系起来,并通过设计扩散张量的两个本征值来控制光流扩散速度。最后采用多分辨率分层细化策略解决大位移问题。实验结果证明,该计算模型在背景复杂、光照变化、运动边界等情况的光流计算具有很好的效果。

In this paper,a computation technology of variational optical flow based on Image-and Flow-driven is proposed. The idea to obtain the data term is to use the combination of gray and gradient constancy assumption,the combination of local and global constraint ,as well as the regularization factor,to improve the accuracy. A joint image-and flow-drive anisotropic smoothing strategy is introduced to design the smooth term,linking the data term and smooth term closely. And then ,the speed of the optical flow can be controled by the design of the eigenvalues of the diffusion tensor. Finally, the method utilizes the multi-scale hierarchical refinement strategy to handle large displacements problem. The experiment results prove that the model has a good computation effect of optical flow to cope with the problem of additive illumination changes and the boundaries of the moving objects with complicated backgrounds.