Subgrid Variational Optimization Optical Flow Estimation Algorithm for Video Flow Measurement
In this paper,an optimization algorithm based on sub-grid scale is studied on the basis of variable optical flow model,which is used to describe complex fluid flow in image sequences and estimate its two-dimensional velocity field.In order to solve the problem of the lack of sub-grid small-scale structural information in the estimation of variational optical flow based on grid scale,combined with the physical motion law of incompressible fluid,this paper introduces the idea of large eddy simulation,de-composes the instantaneous motion into a large-scale motion term and a small-scale turbulence term in the data item of varia-tional model,and uses Smagorinsky model to solve the small-scale turbulence term.Compared with the traditional Farneback dense optical flow algorithm,the improved Subgrid scale Horn-Schunck optical flow(SGS-HS)algorithm has better results in ve-locity field estimation of turbulence image sequences.In order to make the SGS-HS algorithm equally competent for the open channel flow velocity measurement task,the velocity gradient constraint is used in the regularization term of the model,which is used to improve the accuracy of SGS-HS algorithm in the velocity measurement experiment when the flow direction of the open channel flow field is relatively consistent.The experimental results show that compared with the traditional algorithm,the SGS-HS algorithm has better performance in open channel flow velocity measurement.
万方数据
维普
