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Abstract
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.
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Authors and Affiliations
VASE Laboratory, Computer Science & Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK
Nadia Kanwal, Shoaib Ehsan & Adrian F. Clark
Lahore College for Women University, Pakistan
Nadia Kanwal
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- Shoaib Ehsan
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- Adrian F. Clark
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Dpto. Matematica Aplicada I, Escuaela Técnica Superior de Ingeniería Informática, Universite de Sevilla, Avda. Reina Mercedes, s/n, 41012, Sevilla, Spain
Pedro Real
Departamento de Matemática Aplicada I, Escuela Técnica Superior de Ingeniería Informática, University of Seville, Avenida Reina Mercedes s/n, 41012, Sevilla, Spain
Daniel Diaz-Pernil & Helena Molina-Abril &
Departamento de Didáctica de la Mathemática y de las CC.Experimentales, Escuela Universitaria de, Universidad del País Vasco-Esukal Herriko Unibertsitatea, Ramón y Cajal, 72, 48014, Bilbao, (Bizcaia), Spain
Ainhoa Berciano
Institute of Computer Graphics and Algorithms, Pattern Recognition and Image Processing Group, Vienna University of Technology, Favoritenstraße 9/186-3, 1040, Vienna, Austria
Walter Kropatsch
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Kanwal, N., Ehsan, S., Clark, A.F. (2011). Are Performance Differences of Interest Operators Statistically Significant?. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds) Computer Analysis of Images and Patterns. CAIP 2011. Lecture Notes in Computer Science, vol 6855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23678-5_51
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