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Are Performance Differences of Interest Operators Statistically Significant?

Kanwal, Nadia and Ehsan, Shoaib and Clark, Adrian F (2011) 'Are Performance Differences of Interest Operators Statistically Significant?' In: Real, Pedro and Diaz-Pernil, Daniel and Molina-Abril, Helena and Berciano, Ainhoa and Kropatsch, Walter, (eds.) Computer Analysis of Images and Patterns. Lecture Notes in Computer Science (6855). Springer, pp. 429-436. ISBN 978-3-642-23677-8

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The differences in performance of a range of interest operators are examined in a null hypothesis framework using McNemar’s test on a widely-used database of images, to ascertain whether these apparent differences are statistically significant. It is found that some performance differences are indeed statistically significant, though most of them are at a fairly low level of confidence, i.e. with about a 1-in-20 chance that the results could be due to features of the evaluation database. A new evaluation measure i.e. accurate homography estimation is used to characterize the performance of feature extraction algorithms.Results suggest that operators employing longer descriptors are more reliable.

Item Type: Book Section
Additional Information: 14th International Conference, CAIP 2011, Seville, Spain, August 29-31, 2011, Proceedings, Part II
Uncontrolled Keywords: Feature extraction, homography, McNemar's test
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Clare Chatfield
Date Deposited: 10 Sep 2014 09:27
Last Modified: 10 Sep 2014 09:27

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