Dense matching of two views with large displacement

This paper describes a method of establishing dense matching of two views with large displacements. The problem addressed is formulated as the minimization of an energy functional that combines a similarity term and a smoothness term. The minimization of the energy functional reduces to solving a large system of nonlinear equations which is a discretized version of the Euler-Lagrange equation for the energy minimization problem at each image point. A dense displacement map is computed by solving the system of equations using a coarse-to-fine approach. The method has been successfully experimented with two applications: (1) computing binocular disparities from stereo pair images and (2) computing a dense displacement vector field (optical flow) from two views in a time-varying image sequence