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High-quality depth from uncalibrated small motion clip

Cited 60 time in Web of Science Cited 85 time in Scopus
Authors

Ha, Hyowon; Im, Sunghoon; Park, Jaesik; Jeon, Hae-Gon; Kweon, In So

Issue Date
2016
Publisher
IEEE Computer Society
Citation
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol.2016-December, pp.5413-5421
Abstract
We propose a novel approach that generates a highquality depth map from a set of images captured with a small viewpoint variation, namely small motion clip. As opposed to prior methods that recover scene geometry and camera motions using pre-calibrated cameras, we introduce a self-calibrating bundle adjustment tailored for small motion. This allows our dense stereo algorithm to produce a high-quality depth map for the user without the need for camera calibration. In the dense matching, the distributions of intensity profiles are analyzed to leverage the benefit of having negligible intensity changes within the scene due to the minuscule variation in viewpoint. The depth maps obtained by the proposed framework show accurate and extremely fine structures that are unmatched by previous literature under the same small motion configuration.
ISSN
1063-6919
URI
https://hdl.handle.net/10371/201323
DOI
https://doi.org/10.1109/CVPR.2016.584
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  • College of Engineering
  • Dept. of Computer Science and Engineering
Research Area Computer Graphics, Computer Vision, Machine Learning

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