Semantic and Horizon-Based Feature Matching for Optimal Deep Visual Place Recognition in Waterborne Domains

Luke Thomas, Matt Roach, Alma Rahat, Austin Capsey, Mike Edwards

2024

Abstract

To tackle specific challenges of place recognition in the shoreline image domain, we develop a novel Deep Visual Place Recognition pipeline minimizing redundant feature extraction and maximizing salient feature extraction by exploiting the shoreline horizon. Optimizing for model performance and scalability, we present Semantic and Horizon-Based Matching for Visual Place Recognition (SHM-VPR). Our approach is motivated by the unique nature of waterborne imagery, namely the tendency for salient land features to make up a minority of the overall image, with the rest being disposable sea and sky regions. We initially attempt to exploit this via unsupervised region proposal, but we later propose a horizon-based approach that provides improved performance. We provide objective results on both a novel in-house shoreline dataset and the already established Symphony Lake dataset, with SHM-VPR providing state-of-the-art results on the former.

Paper Citation

in Harvard Style

Thomas L., Roach M., Rahat A., Capsey A. and Edwards M. (2024). Semantic and Horizon-Based Feature Matching for Optimal Deep Visual Place Recognition in Waterborne Domains. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-684-2, SciTePress, pages 761-770. DOI: 10.5220/0012376000003654

in Bibtex Style

@conference{icpram24,
author={Luke Thomas and Matt Roach and Alma Rahat and Austin Capsey and Mike Edwards},
title={Semantic and Horizon-Based Feature Matching for Optimal Deep Visual Place Recognition in Waterborne Domains},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2024},
pages={761-770},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012376000003654},
isbn={978-989-758-684-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Semantic and Horizon-Based Feature Matching for Optimal Deep Visual Place Recognition in Waterborne Domains
SN - 978-989-758-684-2
AU - Thomas L.
AU - Roach M.
AU - Rahat A.
AU - Capsey A.
AU - Edwards M.
PY - 2024
SP - 761
EP - 770
DO - 10.5220/0012376000003654
PB - SciTePress