Zaffar, Mubariz and Ehsan, Shoaib and Milford, Michael and McDonald-Maier, Klaus (2020) 'Memorable Maps: A Framework for Re-defining Places in Visual Place Recognition.' IEEE Transactions on Intelligent Transportation Systems. ISSN 1524-9050

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Abstract

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 criteria 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:	Article
Uncontrolled Keywords:	Visual Place Recognition , memorable maps , ESSEX3IN1 , memorability , staticity
Divisions:	Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User:	Elements
Date Deposited:	02 Jul 2020 15:51
Last Modified:	02 Jul 2020 15:51
URI:	http://repository.essex.ac.uk/id/eprint/27620

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