NDLI: Camera calibration with lens distortion from low-rank textures

Content Provider	IEEE Xplore Digital Library
Author	Zhengdong Zhang Matsushita, Y. Yi Ma
Copyright Year	2011
Description	Author affiliation: Microsoft Research Asia (Matsushita, Y.; Yi Ma) \|\| Tsinghua University, China (Zhengdong Zhang)
Abstract	We present a simple, accurate, and flexible method to calibrate intrinsic parameters of a camera together with (possibly significant) lens distortion. This new method can work under a wide range of practical scenarios: using multiple images of a known pattern, multiple images of an unknown pattern, single or multiple image(s) of multiple patterns, etc. Moreover, this new method does not rely on extracting any low-level features such as corners or edges. It can tolerate considerably large lens distortion, noise, error, illumination and viewpoint change, and still obtain accurate estimation of the camera parameters. The new method leverages on the recent breakthroughs in powerful high-dimensional convex optimization tools, especially those for matrix rank minimization and sparse signal recovery. We will show how the camera calibration problem can be formulated as an important extension to principal component pursuit, and solved by similar techniques. We characterize to exactly what extent the parameters can be recovered in case of ambiguity. We verify the efficacy and accuracy of the proposed algorithm with extensive experiments on real images.
Starting Page	2321
Ending Page	2328
File Size	1767218
Page Count	8
File Format	PDF
ISBN	9781457703942
ISSN	10636919
e-ISBN	9781457703959
DOI	10.1109/CVPR.2011.5995548
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Calibration Lenses Feature extraction Optimization Manganese Lighting
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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