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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Journal of Imaging |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-433X/7/2/25 |
| _version_ | 1797415734256599040 |
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| author | Özgün Yılmaz Camille Simon-Chane Aymeric Histace |
| author_facet | Özgün Yılmaz Camille Simon-Chane Aymeric Histace |
| author_sort | Özgün Yılmaz |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T05:52:45Z |
| format | Article |
| id | doaj.art-f253ff3e835c45018bf46eb779938f56 |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-09T05:52:45Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-f253ff3e835c45018bf46eb779938f562023-12-03T12:16:21ZengMDPI AGJournal of Imaging2313-433X2021-02-01722510.3390/jimaging7020025Evaluation of Event-Based Corner DetectorsÖzgün Yılmaz0Camille Simon-Chane1Aymeric Histace2ETIS UMR 8051, CY Paris Cergy University, ENSEA, CNRS, F95000 Cergy, FranceETIS UMR 8051, CY Paris Cergy University, ENSEA, CNRS, F95000 Cergy, FranceETIS UMR 8051, CY Paris Cergy University, ENSEA, CNRS, F95000 Cergy, FranceBio-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.https://www.mdpi.com/2313-433X/7/2/25event-based cameracorner detectorevent-based corners |
| spellingShingle | Özgün Yılmaz Camille Simon-Chane Aymeric Histace Evaluation of Event-Based Corner Detectors Journal of Imaging event-based camera corner detector event-based corners |
| 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 | event-based camera corner detector event-based corners |
| url | https://www.mdpi.com/2313-433X/7/2/25 |
| work_keys_str_mv | AT ozgunyılmaz evaluationofeventbasedcornerdetectors AT camillesimonchane evaluationofeventbasedcornerdetectors AT aymerichistace evaluationofeventbasedcornerdetectors |