Seamless video composition using optimized mean-value cloning

As the process of pasting a source video patch into a target video sequence, seamless video composition is an important and useful video editing operation. Recently, a novel composition approach based on Mean-Value Coordinates has been presented. However, its composition result is often degraded by smudging and discoloration artifacts. Thus we propose optimized mean-value cloning to eliminate these artifacts by matting technique and interpolation constraint. On the basis of this optimized approach, we further present a new framework for seamless video composition. In the framework, we first develop a propagation model based on contour flow to yield each trimap that provides each frame with a pre-segmentation: definite foreground, definite background and unknown. This propagation model constructs the contour flow of inter-frame by minimizing a cost function, and employs it to relabel the trimap. Moreover, when the trimap propagationmodel is inefficient due to abrupt feature change and complex scene pattern, our framework has also implemented a convenient interactive tool to create and modify trimap. Then, we can use the high-quality trimap to achieve the optimized mean-value cloning. Experimental results demonstrate the effectiveness of our seamless video composition framework.