Zaffar, Mubariz and Ehsan, Shoaib and Milford, Michael and McDonald-Maier, Klaus (2021) 'Memorable Maps: A Framework for Re-defining Places in Visual Place Recognition.' IEEE Transactions on Intelligent Transportation Systems, Early (12). p. 1. 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 |
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| Uncontrolled Keywords: | Visual Place Recognition , memorable maps , ESSEX3IN1 , memorability , staticity |
| 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: | 02 Jul 2020 15:51 |
| Last Modified: | 15 Jan 2022 01:26 |
| URI: | http://repository.essex.ac.uk/id/eprint/27620 |
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