Please use this identifier to cite or link to this item:
https://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 1939-3539 |
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 |
DOI: | 10.1109/TPAMI.2003.1227992 |
Published version: | http://dx.doi.org/10.1109/tpami.2003.1227992 |
Appears in Collections: | Aurora harvest 7 Computer Science publications |
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hdl1328.pdf | 319.36 kB | Publisher's PDF | View/Open |
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