Modelling the optical-flow with projective-transform approximation for large camera movements

The camera movement estimation targets the finding of a projective transformation which links consecutive images. As far as small motion is considered, an approximation of the vector displacement field is calculated from local optical flow following Longuet-Higgins-Prazdny (LHP) model; the camera large movements are usually estimated from pyramidal implementation of optical flow and LHP model. An alternative to this latter-addressed in this paper - aims to model globally the large optical flow vector field in order to obtain a non approximated homographic model which links two images. The projective parameters are obtained using Bellman´s 1D dynamic programming (1D DP) extended to 2D (2D DP) and its pyramidal implementation. The experimental results confirm the better correlation between images matched through the proposed non-approximated homography when compared to other existing local (Lucas-Kanade for example) or semi-global (Horn-Schunck for example) approaches.