Mutual information for Lucas-Kanade tracking (MILK): An inverse compositional formulation
Mutual Information (MI) is popular for registration via function optimization. This work proposes an inverse compositional formulation of MI for Levenberg-Marquardt optimization. This yields a constant Hessian, which may be precomputed. Speed improvements of 15 percent were obtained, with convergence accuracies similar those of the standard formulation.
mutual information tracking registration newton optimization