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Video composition by optimized 3D mean-value coordinates


Yan Gao, East China Normal University, Shanghai, China.



In this paper, we propose a new video composition method by 3D mean-value coordinate (MVC). 2D MVCs have been widely used in image composition; however, when 2D MVC is applied to a video sequence directly, because of over-blending and the lack of temporal consistency, some unnatural effects may appear in the final composite results. Although 3D Poisson editing can maintain spatial and temporal consistency, it also leads to high algorithm complexity. Instead of 3D Poisson editing, we use the 3D MVC to seamlessly blend a given source video patch into a target video sequence; this approach is able to achieve high-performance blending with less computation. We show that the combination of alpha matte-based approaches and our method can further refine the produced video when the boundaries of the source object and the target object are very different. Our algorithm can be paralleled and run on a graphics processing unit. The experimental results show that our method is effective and efficient. Copyright © 2012 John Wiley & Sons, Ltd.

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