汽车工业
计算机科学
事件(粒子物理)
背景(考古学)
复杂事件处理
高级驾驶员辅助系统
实时计算
嵌入式系统
人工智能
工程类
过程(计算)
操作系统
物理
航空航天工程
古生物学
生物
量子力学
作者
Waseem Shariff,Mehdi Sefidgar Dilmaghani,Paul Kielty,Mohamed Moustafa,Joseph Lemley,Peter Corcoran
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:12: 51275-51306
被引量:32
标识
DOI:10.1109/access.2024.3386032
摘要
Event cameras (EC) represent a paradigm shift and are emerging as valuable tools in the automotive industry, particularly for in-cabin and out-of-cabin monitoring. These cameras capture pixel intensity changes as ”events” with ultra-low latency, making them suitable for real- time applications. In the context of in-cabin monitoring, EC offer solution for driver and passenger tracking, enhancing safety and comfort. For out-of-cabin monitoring, they excel in tracking objects and detecting potential hazards on the road. This article explores the applications, benefits, and challenges of event cameras in these two critical domains within the automotive industry. This review also highlights relevant datasets and methodologies, enabling researchers to make informed decisions tailored to their specific vehicular-technology and place their work in the broader context of EC sensing. Through an exploration of the hardware, the complexities of data processing, and customized algorithms for both in-cabin and out-of-cabin surveillance, this paper outlines a framework encompassing methodologies, tools, and datasets critical for the implementation of event camera sensing in automotive systems.
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