FNS, CFNS and HEIV: A Unifying Approach
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Estimation of parameters from image tokens is a central problem in computer vision. FNS, CFNS and HEIV are three recently developed methods for solving special but important cases of this problem. The schemes are means for finding unconstrained (FNS, HEIV) and constrained (CFNS) minimisers of cost functions. In earlier work of the authors, FNS, CFNS and a core version of HEIV were applied to a specific cost function. Here we extend the approach to more general cost functions. This allows the FNS, CFNS and HEIV methods to be placed within a common framework.
Keywordsstatistical methods maximum likelihood (un)constrained minimisation fundamental matrix epipolar equation conic fitting
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- 1.M.J. Brooks, W. Chojnacki, and L. Baumela, “Determining the egomotion of an uncalibrated camera from instantaneous optical flow,” Journal of the Optical Society of America A, Vol. 14, No. 10, pp. 2670–2677, 1997.Google Scholar
- 5.O.D. Faugeras, Three-Dimensional Computer Vision: A Geometric Viewpoint, MIT Press: Cambridge, MA, 1993.Google Scholar
- 7.K. Kanatani, Statistical Optimization for Geometric Computation: Theory and Practice, Elsevier: Amsterdam, 1996.Google Scholar
- 9.B. Matei, “Heteroscedastic errors-in-variables models in computer vision,” PhD thesis, Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, May 2001. Available at http://www.caip.rutgers.edu/riul/research/theses.html.
- 10.B. Matei and P. Meer, “A general method for errors-in-variables problems in computer vision,” in Proceedings, CVPR 2000, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Hilton Head Island, South Carolina, 2000, IEEE Computer Society Press: Los Alamitos, CA, 2000, Vol. 2, pp. 18–25.Google Scholar
- 12.A. van den Hengel, W. Chojnacki, M.J. Brooks, and D. Gawley, “A new constrained parameter estimator: experiments in fundamental matrix computation,” in Proceedings of the 13th British Machine Vision Conference, P.L. Rosin, D. Marshall (eds.), Cardiff, England, 2-5 September, 2002, BMVA Press, 2002. Vol. 2, pp. 468–476.Google Scholar