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Fast, Compact and Discriminative: Evaluation of Binary Descriptors for Mobile Applications

Madeo, S and Bober, MZ (2016) Fast, Compact and Discriminative: Evaluation of Binary Descriptors for Mobile Applications IEEE Transactions on Multimedia.

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Abstract

Local feature descriptors underpin many diverse applications, supporting object recognition, image registration, database search, 3D reconstruction and more. The recent phenomenal growth in mobile devices and mobile computing in general has created demand for descriptors that are not only discriminative, but also compact in size and fast to extract and match. In response, a large number of binary descriptors have been proposed, each claiming to overcome some limitations of the predecessors. This paper provides a comprehensive evaluation of several promising binary designs. We show that existing evaluation methodologies are not sufficient to fully characterize descriptors’ performance and propose a new evaluation protocol and a challenging dataset. In contrast to the previous reviews, we investigate the effects of the matching criteria, operating points and compaction methods, showing that they all have a major impact on the systems’ design and performance. Finally, we provide descriptor extraction times for both general-purpose systems and mobile devices, in order to better understand the real complexity of the extraction task. The objective is to provide a comprehensive reference and a guide that will help in selection and design of the future descriptors.

Item Type: Article
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Madeo, SUNSPECIFIEDUNSPECIFIED
Bober, MZUNSPECIFIEDUNSPECIFIED
Date : 5 October 2016
Identification Number : https://doi.org/10.1109/TMM.2016.2615521
Copyright Disclaimer : © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 25 Oct 2016 13:56
Last Modified : 25 Oct 2016 13:58
URI: http://epubs.surrey.ac.uk/id/eprint/812598

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