An improved optical flow algorithm based on image and flow-driven regularization

Variational methods are among the most accurate techniques for estimating the optic flow. In this paper, an estimation technology of variational optical flow based on Image and Flow-driven regularization methods are introduced to preserve the discontinuities and yield dense flow fields. Additionally, variational frame work together with the image pyramid and gaussian filter method are applied in the solving process to estimate large displacements correctly. The data term of the energy model includes brightness and gradient constancy assumption. Experimental results prove that the method is improved to a certain extent compared with the previous variational model of optical.