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High-quality depth from uncalibrated small motion clip

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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.
Author(s)
Ha, HyowonIm, SunghoonPark, JaesikJeon, Hae-GonKweon, In So
Issued Date
2016-06-28
Type
Conference Paper
DOI
10.1109/CVPR.2016.584
URI
https://scholar.gist.ac.kr/handle/local/20626
Publisher
IEEE Computer Society
Citation
29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, pp.5413 - 5421
Conference Place
US
Las Vegas, NV, USA
Appears in Collections:
Department of AI Convergence > 2. Conference Papers
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