High-quality depth from uncalibrated small motion clip
- 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, Hyowon; Im, Sunghoon; Park, Jaesik; Jeon, Hae-Gon; Kweon, 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
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Appears in Collections:
- Department of AI Convergence > 2. Conference Papers
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