On Convergence of the Horn and Schunck Optical-Flow Estimation Method

The purpose of this study is to prove convergence results for the Horn and Schunck optical-flow estimation method. Horn and Schunck stated optical-flow estimation as the minimization of a functional. When discretized, the corresponding Euler–Lagrange equations form a linear system of equations. We write explicitly this system and order the equations in such a way that its matrix is symmetric positive definite. This property implies the convergence Gauss–Seidel iterative resolution method, but does not afford a conclusion on the convergence of the Jacobi method. However, we prove directly that this method also converges. We also show that the matrix of the linear system is block tridiagonal. The blockwise iterations corresponding to this block tridiagonal structure converge for both the Jacobi and the Gauss-Seidel methods, and the Gauss–Seidel method is faster than the (sequential) Jacobi method.