Research Repository

Are performance differences of interest operators statistically significant?

UNSPECIFIED (2011) Are performance differences of interest operators statistically significant? In: UNSPECIFIED, ? - ?.

Full text not available from this repository.

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. © 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)
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: 24 Jan 2015 21:40
Last Modified: 08 Jan 2019 19:15
URI: http://repository.essex.ac.uk/id/eprint/9212

Actions (login required)

View Item View Item