Abstract
Video inpainting describes the process of removing a portion of a video and filling in the missing part (hole) in a visually consistent manner. Most existing video inpainting techniques are computationally intensive and cannot handle large holes. In this paper, we propose a complete and efficient video in-painting system. Our system applies different strategies to handle static and dynamic portions of the hole. To inpaint the static portion, our system uses background replacement and image inpainting techniques. To inpaint moving objects in the hole, we utilizes background subtraction and object segmentation to extract a set of object templates and perform optimal object interpolation using dynamic programming. We evaluate the performance of our system based on a set of indoor surveillance sequences with different types of occlusions.
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