NDLI: Linear approaches to camera calibration from sphere images or active intrinsic calibration using vanishing points

Content Provider	IEEE Xplore Digital Library
Author	Xianghua Ying Hongbin Zha
Copyright Year	2005
Description	Author affiliation: Nat. Lab. on Machine Perception, Peking Univ., Being, China (Xianghua Ying; Hongbin Zha)
Abstract	Spherical objects and vanish points are often used for camera calibration. An occluding contour of a sphere is projected to a conic in the perspective image, and using a moving active camera, the trajectory of a vanishing point in the perspective images is also a conic when the camera is rotated about a fixed 3D axis whereas the translation of the camera is arbitrary. In fact, the problems of camera calibration using conics from spheres or vanishing points can be described by same mathematic representations. Two linear approaches to the problems are proposed in this paper: one based on the geometric interpretation of the relation between image conics and the image of the absolute conic, and the other using the special structure of the problems in algebra. Only three such conics are needed for the two linear approaches, and the minimum number for previous nonlinear optimization methods is also three. All five intrinsic parameters are recovered linearly without making assumptions, such as, zero-skew or unitary aspect ratio which are often used in previous methods. The two linear algorithms have been tested in extensive experiments with respect to noise sensitivity and also made comparisons with recent calibration techniques.
Sponsorship	IEEE Comput. Soc. Tech. Comm. on Pattern Anal. and Machine Intelligence
Starting Page	596
Ending Page	603
File Size	230411
Page Count	8
File Format	PDF
ISBN	076952334X
ISSN	15505499
DOI	10.1109/ICCV.2005.145
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Calibration Cameras Mathematics Laboratories Algebra Optimization methods Testing Optical imaging Optical sensors Computer vision
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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