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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: UNSPECIFIED, ? - ?.

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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. © 2011 Springer-Verlag.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Uncontrolled Keywords: Feature Extraction; Homography; McNemar's Test
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 24 Jan 2015 21:40
Last Modified: 23 Sep 2022 18:27

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