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Numerical Methods for Model-Based Pose Recovery
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@TechReport{Carceroni:TR97b,
  author = 	 {Rodrigo L. Carceroni and Christopher M. Brown},
  title = 	 {Numerical Methods for Model-Based Pose Recovery},
  institution =  {Comp. Sci. Dept. University of Rochester},
  year = 	 {1997},
  number = 	 {659},
  address = 	 {Rochester NY},
  month = 	 {August},
  abstract =   { 
In this paper we review and compare several techniques for model-based pose 
recovery (extrinsic camera calibration) from monocular images. We classify the 
solutions reported in the literature as analytical perspective, affine and 
numerical perspective. We also present reformulations for two of the most 
important numerical perspective solutions: Lowe's algorithm and Phong-Horaud's
algorithm. Our improvement to Lowe's algorithm consists of eliminating some 
simplifying assumptions on its projective equations. A careful experimental 
evaluation reveals that the resulting fully projective algorithm has 
superexponential convergence properties for a wide range of initial solutions 
and, under realistic usage conditions, it is up to an order of magnitude more 
accurate than the original formulation, with arguably better computation-time 
properties. Our extension to Phong-Horaud's algorithm is, to the best of our 
knowledge, the first method for independent orientation recovery that actually 
exploits the theoretical advantages of point correspondences over line 
correspondences. We show that in the context of a specific real-life application
(visual navigation), it is either more accurate than other similar techniques 
with the same computational cost, or more efficient with the same accuracy.   }
}