Research Repository

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 (Unpublished)

[img]
Preview
Text
1811.03529v2.pdf

Download (3MB) | Preview

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 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.CV, cs.RO
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 19 Jun 2020 08:27
Last Modified: 19 Jun 2020 08:27
URI: http://repository.essex.ac.uk/id/eprint/27929

Actions (login required)

View Item View Item