Fast motion estimation using Bidirectional Gradient Methods

Gradient based motion estimation techniques (GM) are considered to be in the heart of state-of-the-art registration algorithms [2], being able to account for both pixel and subpixel registration and to handle various motion models (translation, rotation, affine, projective). These methods estimate the motion between two images based on the local changes in the image intensities while assuming image smoothness. This paper introduces two new bidirectional formulations of the GM, improving the convergence properties for large motions. Experimental results demonstrate the applicability of these algorithms to real images.