DocumentCode
639428
Title
Single Image Calibration of Multi-axial Imaging Systems
Author
Agrawal, Ankit ; Ramalingam, S.
Author_Institution
Mitsubishi Electr. Res. Labs. (MERL), Cambridge, MA, USA
fYear
2013
fDate
23-28 June 2013
Firstpage
1399
Lastpage
1406
Abstract
Imaging systems consisting of a camera looking at multiple spherical mirrors (reflection) or multiple refractive spheres (refraction) have been used for wide-angle imaging applications. We describe such setups as multi-axial imaging systems, since a single sphere results in an axial system. Assuming an internally calibrated camera, calibration of such multi-axial systems involves estimating the sphere radii and locations in the camera coordinate system. However, previous calibration approaches require manual intervention or constrained setups. We present a fully automatic approach using a single photo of a 2D calibration grid. The pose of the calibration grid is assumed to be unknown and is also recovered. Our approach can handle unconstrained setups, where the mirrors/refractive balls can be arranged in any fashion, not necessarily on a grid. The axial nature of rays allows us to compute the axis of each sphere separately. We then show that by choosing rays from two or more spheres, the unknown pose of the calibration grid can be obtained linearly and independently of sphere radii and locations. Knowing the pose, we derive analytical solutions for obtaining the sphere radius and location. This leads to an interesting result that 6-DOF pose estimation of a multi-axial camera can be done without the knowledge of full calibration. Simulations and real experiments demonstrate the applicability of our algorithm.
Keywords
calibration; cameras; mirrors; optical images; 2D calibration grid; 6-DOF pose estimation; camera coordinate system; internally calibrated camera; multiaxial imaging systems; multiple refractive spheres; multiple spherical mirrors; refractive balls; single image calibration; wide-angle imaging applications; Calibration; Cameras; Equations; Estimation; Mirrors; Noise; axial; calibration; catadioptric; spherical mirror; wide-angle;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location
Portland, OR
ISSN
1063-6919
Type
conf
DOI
10.1109/CVPR.2013.184
Filename
6619028
Link To Document