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Title: Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation
Authors: Peñate Sánchez, Adrián 
Andrade-Cetto, Juan
Moreno-Noguer, Francesc
UNESCO Clasification: 1203 Ciencia de los ordenadores
Keywords: Camera calibration
Perspective-n-point problem
Issue Date: 2013
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence 
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focal length as an additional unknown renders the linearization and relinearization techniques of the original approach no longer valid, especially with large amounts of noise.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.
ISSN: 0162-8828
DOI: 10.1109/TPAMI.2013.36
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence [ISSN 0162-8828], v. 35 (10), p. 2387-2400, (Octubre 2013)
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