Newton-type algorithms for time-varying pose estimation

Author

Baumann, Markus ; Lageman, Christian ; Helmke, Uwe

Author_Institution

Math. Inst., Wurzburg Univ., Germany

fYear

2004

fDate

14-17 Dec. 2004

Firstpage

155

Lastpage

160

Abstract

In this paper we consider the task of pose estimation for a rigid configuration of N moving points in R³, based on camera image point data. Since the Euclidean motion parameters are uniquely determined, up to a scalar factor, by the associated essential matrices, we focus on the estimation task for essential matrices. After a reformulation as a constrained optimization problem for a time-varying family of cost functions, a Newton-type path following method is applied to asymptotically track the minima of the cost functions. A discretization of a damped Newton method in a 12-dimensional parameter space is proposed that tracks the time-varying essential matrices up to first order.

Keywords

Newton method; computer vision; matrix algebra; motion estimation; optimisation; parameter estimation; time-varying systems; tracking; 12-dimensional parameter space; Euclidean motion parameters; Newton-type path following; asymptotic tracking; camera image point data; constrained optimization problem; cost function minima; damped Newton method; essential matrices; time-varying cost functions; time-varying pose estimation; Australia; Cameras; Computational geometry; Computer vision; Constraint optimization; Cost function; Image reconstruction; Motion estimation; Newton method; Stereo vision;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004

Print_ISBN

0-7803-8894-1

Type

conf

DOI

10.1109/ISSNIP.2004.1417454

Filename

1417454