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Memorable Maps: A Framework for Re-defining Places in Visual Place Recognition

Zaffar, Mubariz and Ehsan, Shoaib and Milford, Michael and McDonald-Maier, Klaus (2019) Memorable Maps: A Framework for Re-defining Places in Visual Place Recognition. Working Paper. arXiv. (Unpublished)


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This paper presents a cognition-inspired agnostic framework for building a map for Visual Place Recognition. This framework draws inspiration from human-memorability, utilizes the traditional image entropy concept and computes the static content in an image; thereby presenting a tri-folded criterion to assess the 'memorability' of an image for visual place recognition. A dataset namely 'ESSEX3IN1' is created, composed of highly confusing images from indoor, outdoor and natural scenes for analysis. When used in conjunction with state-of-the-art visual place recognition methods, the proposed framework provides significant performance boost to these techniques, as evidenced by results on ESSEX3IN1 and other public datasets.

Item Type: Monograph (Working Paper)
Additional Information: 13 pages, 25 figures, 1 table
Uncontrolled Keywords: cs.CV; cs.RO
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 19 Jun 2020 08:27
Last Modified: 15 Jan 2022 01:34

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