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Automatic Selection of the Optimal Local Feature Detector

Ferrarini, Bruno and Ehsan, Shoaib and Rehman, Naveed Ur and Leonardis, Ales̆ and McDonald-Maier, Klaus D (2016) Automatic Selection of the Optimal Local Feature Detector. In: 13th International Conference on Image Analysis and Recognition, ICIAR 2016, 2016-07-13 - 2016-07-15, Póvoa de Varzim, Portugal.

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Abstract

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: Image Analysis and Recognition 13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel, Póvoa de Varzim, Portugal, July 13-15, 2016, Proceedings
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: 28 May 2020 16:59
URI: http://repository.essex.ac.uk/id/eprint/18160

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