Real-time global motion estimation for video stabilization

Touraj Tajbakhsh

Abstract: Digital video stabilization is a cost-effective way to reduce the effect of camera shake in handheld video cameras. We propose several enhancements for video stabilization based on integral projection matching,1 which is a simple and efficient global motion estimation technique for translational motion. One-dimensional intensity projections along the horizontal and vertical axes provide a signature of the image. Global motion estimation aims at finding the largest similarity between shifted intensity projections between consecutive frames. The obtained shifts provide information about the global inter-frame motion. Relying upon the estimated global motion an output frame of reduced size is determined deploying motion smoothing. We propose several enhancements of prior works to improve the stabilization performance and to reduce computational complexity and memory requirements. The main enhancement is a partitioning of the projection intensities to better cope with in-scene motion. Logarithmic search is deployed to seek for a minimum matching error for selected partitions in two subsequent frames. Furthermore we propose a novel motion smoothing approach we call center-attracted motion damping. We evaluate the performance of the enhancements under various imaging conditions using real video sequences as well as synthetic video sequences with provided ground-truth motion. The stabilization accuracy is sufficient under most imaging conditions so that the effect of camera shake is eliminated or significantly reduced in the stabilized video.