@inproceedings{373ff1258e8c496c8a017eb2c72845f7,
title = "Automatic inpainting of linearly related video frames",
abstract = "This paper addresses automatic inpainting of a specific but common kind of videos captured by imaging a far or planar scene with a moving camera. The projective model tells that the frames of such videos can be approximately aligned by linear mappings except for some to-be-inpainted small regions. Mathematically, we treat inpainting as a global optimization with a linear system incorporating both the temporal consistency and the priors of the inpainting regions: (i) temporally registered frames form a low rank matrix; (ii) the pixels in the given inpainting regions destroy the low rank-ness with gross sparse errors. Besides, we also use a soft mask to ensure consistent global brightness before and after inpainting. Further, we propose a numerical solution to above optimization based on Augmented Lagrangian Method. The experiment results demonstrated our advantageous in both preserving thin scene structures and the details prone to be smoothed out by previous methods.",
keywords = "Video inpainting, low rank, sparse",
author = "Yudong Xiao and Jinli Suo and Liheng Bian and Lei Zhang and Qionghai Dai",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.",
year = "2014",
month = jan,
day = "28",
doi = "10.1109/ICIP.2014.7025951",
language = "English",
series = "2014 IEEE International Conference on Image Processing, ICIP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4692--4696",
booktitle = "2014 IEEE International Conference on Image Processing, ICIP 2014",
address = "United States",
}