Multi-view 3D Reconstruction from Uncalibrated Radially-Symmetric Cameras

Jae-Hak Kim, Yuchao Dai, Hongdong Li, Xin Du, Jonghyuk Kim; The IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1896-1903

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 omnidirectional 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.

Related Material


[pdf]
[bibtex]
@InProceedings{Kim_2013_ICCV,
author = {Kim, Jae-Hak and Dai, Yuchao and Li, Hongdong and Du, Xin and Kim, Jonghyuk},
title = {Multi-view 3D Reconstruction from Uncalibrated Radially-Symmetric Cameras},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}
}