Title : 
Newton-type algorithms for time-varying pose estimation
         
        
            Author : 
Baumann, Markus ; Lageman, Christian ; Helmke, Uwe
         
        
            Author_Institution : 
Math. Inst., Wurzburg Univ., Germany
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
         
        
            Print_ISBN : 
0-7803-8894-1
         
        
        
            DOI : 
10.1109/ISSNIP.2004.1417454