Publication
Exhaustive linearization for robust camera pose and focal length estimation
Journal Article (2013)
Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pages
2387-2400
Volume
35
Number
10
Doc link
http://dx.doi.org/10.1109/TPAMI.2013.36
File
Abstract
We propose a novel approach for the estimation of the pose and focal length of a camera from a set of 3D-to-2D point correspondences. Our method compares favorably to competing approaches in that it is both more accurate than existing closed form solutions, as well as faster and also more accurate than iterative ones. Our approach is inspired on the EPnP algorithm, a recent O(n) solution for the calibrated case. Yet, we show that considering the focal length as an additional unknown renders the linearization and relinearization techniques of the original approach no longer valid, especially with large amounts of noise. We present new methodologies to circumvent this limitation termed exhaustive linearization and exhaustive relinearization which perform a systematic exploration of the solution space in closed form. The method is evaluated on both real and synthetic data, and our results show that besides producing precise focal length estimation, the retrieved camera pose is almost as accurate as the one computed using the EPnP, which assumes a calibrated camera.
Categories
computer vision.
Author keywords
camera calibration, perspective-n-point problem
Scientific reference
A. Penate-Sanchez, J. Andrade-Cetto and F. Moreno-Noguer. Exhaustive linearization for robust camera pose and focal length estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(10): 2387-2400, 2013.
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