## Fast and Globally Convergent Pose Estimation From Video Images (1998)

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Citations: | 111 - 5 self |

### BibTeX

@MISC{Lu98fastand,

author = {Chien-ping Lu and Gregory D. Hager and Eric Mjolsness},

title = {Fast and Globally Convergent Pose Estimation From Video Images},

year = {1998}

}

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### Abstract

Determining the rigid transformation relating 2D images to known 3D geometry is a classical problem in photogrammetry and computer vision. Heretofore, the best methods for solving the problem have relied on iterative optimization methods which cannot be proven to converge and/or which do not effectively account for the orthonormal structure of rotation matrices. We show that the pose estimation problem can be formulated as that of minimizing an error metric based on collinearity in object (as opposed to image) space. Using object space collinearity error, we derive an iterative algorithm which directly computes orthogonal rotation matrices and which is globally convergent. Experimentally, we show that the method is computationally efficient, that it is no less accurate than the best currently employed optimization methods, and that it outperforms all tested methods in robustness to outliers. Chien-Ping Lu, Silicon Graphics Inc. cplu@engr.sgi.com y Greg Hager, Department of Computer...

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Citation Context ...thods for pose estimation has been developed by relaxing the orthogonality constraint on rotation matrices and/or by simplifying the perspective camera model [18], [19], [20], [21], [22], [23], [24], =-=[25]-=-. In iterative reduced perspective methods [23], [26], an approximate solution computed using a simplified camera model is iteratively refined to approach a full perspective solution. In these methods... |

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Citation Context ... fourth- or fifth-degree polynomial system can be formulated using geometrical invariants of the observed points and the problem can be solved by finding roots of the polynomial system [7], [8], [9], =-=[10]-=-, [11], [12]. However, the resulting methods can only be applied to a limited number of points and are thus sensitive to additive noise and possible outliers. For more than four points, closed form so... |

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Citation Context ...puter graphics, it plays a central role in tasks that combine computer-generated objects with photographic scenesÐe.g., landmark tracking for determining head pose in augmented reality [2], [3], [4], =-=[5]-=- or interactive manipulation of objects. In computer vision, pose estimation is central to many approaches to object recognition [6]. The information available for solving the pose estimation problem ... |

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ªOptimal Motion and Structure Estimation,º
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- 1993
(Show Context)
Citation Context ...ALLY CONVERGENT POSE ESTIMATION FROM VIDEO IMAGES 613 Gauss-Newton method. It has become a standard technique for nonlinear least-squares problems and has been widely adopted in computer vision [30], =-=[31]-=- and computer graphics [3]. 2.3 Why Another Iterative Algorithm? Classical optimization techniques are currently the only choice when observed data is noisy and a high accuracy solution to the pose es... |