Circular block matching based video stabilization

Video sequences captured by handheld digital camera need to be stabilized to eliminate the tiresome effects caused by camera's undesirable shake or jiggle. The key issue of video stabilization is to estimate the global motion parameters between two successive frames. In this paper, a novel circular block matching algorithm is proposed to estimate the global motion parameters. This algorithm can deal with not only translational motion but even large rotational motion. For an appointed circular block in current frame, a four-dimensional rotation invariant feature vector is firstly extracted from it and used to judge if it is an effective block. Then the rotation invariant features based circular block matching process is performed to find the best matching blocks in reference frame for those effective blocks. With the matching results of any two effective blocks, a two-dimensional motion model is constructed to produce one group of frame motion parameters. A statistical method is proposed to calculate the estimated global motion parameters with all groups of global motion parameters. Finally, using the estimated motion parameters as the initial values, an iteration algorithm is introduced to obtain the refined global motion parameters. The experimental results show that the proposed algorithm is excellent in stabilizing frames with even burst global translational and rotational motions.