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Kim, Kwang In
Machine Learning and Vision Lab.
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Background inpainting for videos with dynamic objects and a free-moving camera

Author(s)
Granados, MiguelKim, Kwang InTompkin, JamesKautz, JanTheobalt, Christian
Issued Date
2012-10-07
DOI
10.1007/978-3-642-33718-5_49
URI
https://scholarworks.unist.ac.kr/handle/201301/32627
Fulltext
https://link.springer.com/chapter/10.1007%2F978-3-642-33718-5_49
Citation
European Conference on Computer Vision, pp.682 - 695
Abstract
We propose a method for removing marked dynamic objects from videos captured with a free-moving camera, so long as the objects occlude parts of the scene with a static background. Our approach takes as input a video, a mask marking the object to be removed, and a mask marking the dynamic objects to remain in the scene. To inpaint a frame, we align other candidate frames in which parts of the missing region are visible. Among these candidates, a single source is chosen to fill each pixel so that the final arrangement is color-consistent. Intensity differences between sources are smoothed using gradient domain fusion. Our frame alignment process assumes that the scene can be approximated using piecewise planar geometry: A set of homographies is estimated for each frame pair, and one each is selected for aligning pixels such that the color-discrepancy is minimized and the epipolar constraints are maintained. We provide experimental validation with several real-world video sequences to demonstrate that, unlike in previous work, inpainting videos shot with free-moving cameras does not necessarily require estimation of absolute camera positions and per-frame per-pixel depth maps. © 2012 Springer-Verlag.
Publisher
12th European Conference on Computer Vision, ECCV 2012
ISSN
0302-9743

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