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Evaluation of Event-Based Corner Detectors
Bio-inspired Event-Based (EB) cameras are a promising new technology that outperforms standard frame-based cameras in extreme lighted and fast moving scenes. Already, a number of EB corner detection techniques have been developed; however, the performance of these EB corner detectors has only been e...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321277/ https://www.ncbi.nlm.nih.gov/pubmed/34460624 http://dx.doi.org/10.3390/jimaging7020025 |
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author | Yılmaz, Özgün Simon-Chane, Camille Histace, Aymeric |
author_facet | Yılmaz, Özgün Simon-Chane, Camille Histace, Aymeric |
author_sort | Yılmaz, Özgün |
collection | PubMed |
description | Bio-inspired Event-Based (EB) cameras are a promising new technology that outperforms standard frame-based cameras in extreme lighted and fast moving scenes. Already, a number of EB corner detection techniques have been developed; however, the performance of these EB corner detectors has only been evaluated based on a few author-selected criteria rather than on a unified common basis, as proposed here. Moreover, their experimental conditions are mainly limited to less interesting operational regions of the EB camera (on which frame-based cameras can also operate), and some of the criteria, by definition, could not distinguish if the detector had any systematic bias. In this paper, we evaluate five of the seven existing EB corner detectors on a public dataset including extreme illumination conditions that have not been investigated before. Moreover, this evaluation is the first of its kind in terms of analysing not only such a high number of detectors, but also applying a unified procedure for all. Contrary to previous assessments, we employed both the intensity and trajectory information within the public dataset rather than only one of them. We show that a rigorous comparison among EB detectors can be performed without tedious manual labelling and even with challenging acquisition conditions. This study thus proposes the first standard unified EB corner evaluation procedure, which will enable better understanding of the underlying mechanisms of EB cameras and can therefore lead to more efficient EB corner detection techniques. |
format | Online Article Text |
id | pubmed-8321277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83212772021-08-26 Evaluation of Event-Based Corner Detectors Yılmaz, Özgün Simon-Chane, Camille Histace, Aymeric J Imaging Article Bio-inspired Event-Based (EB) cameras are a promising new technology that outperforms standard frame-based cameras in extreme lighted and fast moving scenes. Already, a number of EB corner detection techniques have been developed; however, the performance of these EB corner detectors has only been evaluated based on a few author-selected criteria rather than on a unified common basis, as proposed here. Moreover, their experimental conditions are mainly limited to less interesting operational regions of the EB camera (on which frame-based cameras can also operate), and some of the criteria, by definition, could not distinguish if the detector had any systematic bias. In this paper, we evaluate five of the seven existing EB corner detectors on a public dataset including extreme illumination conditions that have not been investigated before. Moreover, this evaluation is the first of its kind in terms of analysing not only such a high number of detectors, but also applying a unified procedure for all. Contrary to previous assessments, we employed both the intensity and trajectory information within the public dataset rather than only one of them. We show that a rigorous comparison among EB detectors can be performed without tedious manual labelling and even with challenging acquisition conditions. This study thus proposes the first standard unified EB corner evaluation procedure, which will enable better understanding of the underlying mechanisms of EB cameras and can therefore lead to more efficient EB corner detection techniques. MDPI 2021-02-03 /pmc/articles/PMC8321277/ /pubmed/34460624 http://dx.doi.org/10.3390/jimaging7020025 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Yılmaz, Özgün Simon-Chane, Camille Histace, Aymeric Evaluation of Event-Based Corner Detectors |
title | Evaluation of Event-Based Corner Detectors |
title_full | Evaluation of Event-Based Corner Detectors |
title_fullStr | Evaluation of Event-Based Corner Detectors |
title_full_unstemmed | Evaluation of Event-Based Corner Detectors |
title_short | Evaluation of Event-Based Corner Detectors |
title_sort | evaluation of event-based corner detectors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321277/ https://www.ncbi.nlm.nih.gov/pubmed/34460624 http://dx.doi.org/10.3390/jimaging7020025 |
work_keys_str_mv | AT yılmazozgun evaluationofeventbasedcornerdetectors AT simonchanecamille evaluationofeventbasedcornerdetectors AT histaceaymeric evaluationofeventbasedcornerdetectors |