Space-Time Video Completion

This paper presents a new framework for completion of missing information based on local structures. It poses the task of completion as a global optimization problem with a well-defined objective function and derives a new algorithm to optimize it. Missing values are constrained to form coherent structures with respect to reference examples.

We apply this method to space-time completion of large space-time “holes” in video sequences of complex dynamic scenes. The missing portions are filled in by sampling spatio-temporal patches from the available parts of the video, while enforcing global spatio-temporal consistency between all patches in and around the hole. The consistent completion of static scene parts simultaneously with dynamic behaviors leads to realistic looking video sequences and images.

Space-time video completion is useful for a variety of tasks, including, but not limited to: (i) Sophisticated video removal (of undesired static or dynamic objects) by completing the appropriate static or dynamic background information, (ii) Correction of missing/corrupted video frames in old movies, (iii) Modifying a visual story by replacing unwanted elements, (iv) Creation of video textures by extending smaller ones, (v) Creation of complete field-of-view stabilized video, and (vi) As images are one-frame videos, we apply the method to this special case as well.