Multi-view 3D reconstruction from uncalibrated radially-symmetric cameras
Date
2013
Authors
Kim, J.-H.
Dai, Y.
Li, H.
Du, X.
Kim, J.
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Conference paper
Citation
Proceedings / IEEE International Conference on Computer Vision. IEEE International Conference on Computer Vision, 2013, pp.1896-1903
Statement of Responsibility
Jae-Hak Kim, Yuchao Dai, Hongdong Li, Xin Du, Jonghyuk Kim
Conference Name
IEEE International Conference on Computer Vision (1 Dec 2013 - 8 Dec 2013 : Sydney, NSW)
Abstract
We present a new multi-view 3D Euclidean reconstruction method for arbitrary uncalibrated radially-symmetric cameras, which needs no calibration or any camera model parameters other than radial symmetry. It is built on the radial 1D camera model [25], a unified mathematical abstraction to different types of radially-symmetric cameras. We formulate the problem of multi-view reconstruction for radial 1D cameras as a matrix rank minimization problem. Efficient implementation based on alternating direction continuation is proposed to handle scalability issue for real-world applications. Our method applies to a wide range of omni directional cameras including both dioptric and catadioptric (central and non-central) cameras. Additionally, our method deals with complete and incomplete measurements under a unified framework elegantly. Experiments on both synthetic and real images from various types of cameras validate the superior performance of our new method, in terms of numerical accuracy and robustness.
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© 2013 IEEE