Data-Driven Technology in Event-Based Vision
Event cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness. To maintain these inherent advantages, the trade-off between efficien...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/6689337 |
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| _version_ | 1832568475291222016 |
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| author | Ruolin Sun Dianxi Shi Yongjun Zhang Ruihao Li Ruoxiang Li |
| author_facet | Ruolin Sun Dianxi Shi Yongjun Zhang Ruihao Li Ruoxiang Li |
| author_sort | Ruolin Sun |
| collection | DOAJ |
| description | Event cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness. To maintain these inherent advantages, the trade-off between efficiency and accuracy stands as a priority in event-based algorithms. Thanks to the preponderance of deep learning techniques and the compatibility between bio-inspired spiking neural networks and event-based sensors, data-driven approaches have become a hot spot, which along with the dedicated hardware and datasets constitute an emerging field named event-based data-driven technology. Focusing on data-driven technology in event-based vision, this paper first explicates the operating principle, advantages, and intrinsic nature of event cameras, as well as background knowledge in event-based vision, presenting an overview of this research field. Then, we explain why event-based data-driven technology becomes a research focus, including reasons for the rise of event-based vision and the superiority of data-driven approaches over other event-based algorithms. Current status and future trends of event-based data-driven technology are presented successively in terms of hardware, datasets, and algorithms, providing guidance for future research. Generally, this paper reveals the great prospects of event-based data-driven technology and presents a comprehensive overview of this field, aiming at a more efficient and bio-inspired visual system to extract visual features from the external environment. |
| format | Article |
| id | doaj-art-0d0890fb649b4ea786696448a5c5966a |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-0d0890fb649b4ea786696448a5c5966a2025-02-03T00:58:58ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66893376689337Data-Driven Technology in Event-Based VisionRuolin Sun0Dianxi Shi1Yongjun Zhang2Ruihao Li3Ruoxiang Li4College of Computer, National University of Defense Technology, Changsha, ChinaArtificial Intelligence Research Center, National Innovation Institute of Defense Technology, Beijing, ChinaArtificial Intelligence Research Center, National Innovation Institute of Defense Technology, Beijing, ChinaArtificial Intelligence Research Center, National Innovation Institute of Defense Technology, Beijing, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaEvent cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness. To maintain these inherent advantages, the trade-off between efficiency and accuracy stands as a priority in event-based algorithms. Thanks to the preponderance of deep learning techniques and the compatibility between bio-inspired spiking neural networks and event-based sensors, data-driven approaches have become a hot spot, which along with the dedicated hardware and datasets constitute an emerging field named event-based data-driven technology. Focusing on data-driven technology in event-based vision, this paper first explicates the operating principle, advantages, and intrinsic nature of event cameras, as well as background knowledge in event-based vision, presenting an overview of this research field. Then, we explain why event-based data-driven technology becomes a research focus, including reasons for the rise of event-based vision and the superiority of data-driven approaches over other event-based algorithms. Current status and future trends of event-based data-driven technology are presented successively in terms of hardware, datasets, and algorithms, providing guidance for future research. Generally, this paper reveals the great prospects of event-based data-driven technology and presents a comprehensive overview of this field, aiming at a more efficient and bio-inspired visual system to extract visual features from the external environment.http://dx.doi.org/10.1155/2021/6689337 |
| spellingShingle | Ruolin Sun Dianxi Shi Yongjun Zhang Ruihao Li Ruoxiang Li Data-Driven Technology in Event-Based Vision Complexity |
| title | Data-Driven Technology in Event-Based Vision |
| title_full | Data-Driven Technology in Event-Based Vision |
| title_fullStr | Data-Driven Technology in Event-Based Vision |
| title_full_unstemmed | Data-Driven Technology in Event-Based Vision |
| title_short | Data-Driven Technology in Event-Based Vision |
| title_sort | data driven technology in event based vision |
| url | http://dx.doi.org/10.1155/2021/6689337 |
| work_keys_str_mv | AT ruolinsun datadriventechnologyineventbasedvision AT dianxishi datadriventechnologyineventbasedvision AT yongjunzhang datadriventechnologyineventbasedvision AT ruihaoli datadriventechnologyineventbasedvision AT ruoxiangli datadriventechnologyineventbasedvision |