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Automatic selection of the optimal local feature detector

Ferrarini, B and Ehsan, S and Rehman, NU and Leonardis, A and McDonald-Maier, KD (2016) Automatic selection of the optimal local feature detector. In: UNSPECIFIED, ? - ?.

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© Springer International Publishing Switzerland 2016. A large number of different local feature detectors have been proposed in the last few years. However, each feature detector has its own strengths and weaknesses that limit its use to a specific range of applications. In this paper is presented a tool capable of quickly analysing input images to determine which type and amount of transformation is applied to them and then selecting the optimal feature detector, which is expected to perform the best. The results show that the performance and the fast execution time render the proposed tool suitable for real-world vision applications.

Item Type: Conference or Workshop Item (UNSPECIFIED)
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: Jim Jamieson
Date Deposited: 22 Nov 2016 15:34
Last Modified: 22 Jan 2019 22:15

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