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A statistical rationalisation of Hartley's normalised eight-point algorithm

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4 Author(s)
Chojnacki, W. ; Sch. of Comput. Sci., Adelaide Univ., SA, Australia ; Brooks, M.J. ; van den Hengel, A. ; Gawley, D.

The eight-point algorithm of Hartley occupies an important place in computer vision, notably as a means of providing an initial value of the fundamental matrix for use in iterative estimation methods. In this paper, a novel explanation is given for the improvement in performance of the eight-point algorithm that results from using normalised data. A first step is singling out a cost function that the normalised algorithm acts to minimise. The cost function is then shown to be statistically better founded than the cost function associated with the non-normalised algorithm. This augments the original argument that improved performance is due to the better conditioning of a pivotal matrix. Experimental results are given that support the adopted approach. This work continues a wider effort to place a variety of estimation techniques within a coherent framework.

Published in:

Image Analysis and Processing, 2003.Proceedings. 12th International Conference on

Date of Conference:

17-19 Sept. 2003