Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/1328
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Type: Journal article
Title: Revisiting Hartley's normalized eight-point algorithm
Author: Chojnacki, W.
Brooks, M.
Van Den Hengel, A.
Gawley, D.
Citation: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003; 25(9):1172-1177
Publisher: IEEE Computer Soc
Issue Date: 2003
ISSN: 0162-8828
Statement of
Responsibility: 
Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel and Darren Gawley
Abstract: Hartley's eight-point algorithm has maintained 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 normalized data. It is first established that the normalized algorithm acts to minimize a specific cost function. It is then shown that this cost function I!; statistically better founded than the cost function associated with the nonnormalized 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.
Keywords: Epipolar equation; fundamental matrix; eight-point algorithm; data normalization
Description: Copyright © 2003 IEEE
RMID: 0020030454
DOI: 10.1109/TPAMI.2003.1227992
Appears in Collections:Computer Science publications

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