Fast and Globally Convergent Pose Estimation From Video Images

DMCA

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

Cached

Download Links

Other Repositories/Bibliography

DBLP

by Chien-ping Lu , Gregory D. Hager , Eric Mjolsness

Citations:

151 - 6 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}
}

OpenURL

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...

Keyphrases

iterative optimization method chien-ping lu object space collinearity error optimization method com greg hager computer vision iterative algorithm orthogonal rotation matrix cplu engr rigid transformation rotation matrix classical problem silicon graphic inc orthonormal structure pose estimation problem

DMCA