Two-frame multi-scale optical flow estimation using wavelet decomposition

Abstract

A multi-scale algorithm using wavelet decomposition is proposed to estimate dense optical flow using only two frames. Hierarchical image representation by wavelet decomposition is used to exploit the assumption of local rigid motion in a new multi-scale framework. It is shown that if a wavelet basis with one vanishing moment is carefully selected, we can get hierarchical images, edges, and comers from the wavelet decomposition. Based on this result, all the components of the wavelet decomposition are used to estimate relatively accurate optical flow even under the inadequate image sampling condition, and overcome the “flattening-out” problem in traditional pyramid methods, which produce high errors when low-texture regions become flat at coarse levels due to blurring. Local affine transforms are also used to speed up flow estimation. Experiments on different types of image sequences together with quantitative and qualitative comparisons with several other optical flow methods are given to demonstrate the effectiveness and robustness of our algorithm.