CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2007 vol.29 Issue No.03 - March
Issue No.03 - March (2007 vol.29)
Eli Shechtman , IEEE Computer Society
Michal Irani , IEEE Computer Society
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2007.60
This paper presents a new framework for the 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: 1) Sophisticated video removal (of undesired static or dynamic objects) by completing the appropriate static or dynamic background information. 2) Correction of missing/corrupted video frames in old movies. 3) Modifying a visual story by replacing unwanted elements. 4) Creation of video textures by extending smaller ones. 5) Creation of complete field-of-view stabilized video. 6) As images are one-frame videos, we apply the method to this special case as well.
Video analysis, texture, space-time analysis.
Eli Shechtman, Michal Irani, "Space-Time Completion of Video", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.29, no. 3, pp. 463-476, March 2007, doi:10.1109/TPAMI.2007.60