Abstract

This paper presents a novel formulation of video stabilization by directly solving for optimal image warps toward stabilized sequence. With the estimated shaky motion via long or short feature trajectories, our approach encodes another two steps, motion compensation and image warping, into a single global optimization process, rather than operating as two individual steps. This process is done only with positions of embedded mesh vertices as common variables. Spatial and temporal coherence is therein reformulated with similarity-invariant representation of motion trajectories and intra- (and inter-) frame consistency of similar transformations with respect to mesh vertices. Such a one-shot formulation converts video stabilization into a quadratic energy minimization problem defined for image warps, and thus can be efficiently resolved by using a robust solver for sparse linear systems. Experimental results demonstrate the flexibility and efficiency of our approach in producing visually plausible stabilization effects on a variety of videos.

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