神经形态视觉传感器的硬件、算法与应用：综述
Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: a Review
AI总结：
本文从硬件演进、事件驱动算法和实际应用三个维度系统综述神经形态视觉传感器，并分析其推广挑战与未来研究方向。
摘要：
神经形态相机，即事件相机，代表了经典视觉感知方法的一种转变，它将检测到的瞬时逐像素光照变化编码为异步的事件包流。与标准相机相比，其新颖之处在于从以固定时间间隔捕获完整图像帧转变为稀疏数据格式，这种格式凭借其独特性质，有望在各种应用中带来改进。然而，这些优势的代价是需要重新设计算法流程或对其进行改造，以有效处理新的数据格式。在本综述中，我们从三个主要维度系统地审视神经形态视觉。首先，我们重点介绍神经形态相机从诞生到近期型号的技术演进和独特的硬件特征。其次，我们回顾了专门为基于事件的数据开发的图像处理算法，涵盖特征检测、跟踪和光流方面的关键工作——这些构成了分析图像元素和变换的基础——以及深度与位姿估计或物体识别，这些工作用于解释更复杂的场景结构和组成部分。这些技术源自经典计算机视觉和现代数据驱动方法，我们对它们进行考察，以说明事件相机应用的广度。第三，我们展示了实际应用案例研究，说明事件相机如何在各个行业和场景中得到成功应用。最后，我们分析了限制其广泛采用的挑战，指出了与标准成像技术相比存在的重大研究空白，并概述了神经形态视觉所提供的具有前景的未来方向和机遇。
英文摘要：
Neuromorphic, or event, cameras represent a transformation in the classical approach to visual sensing encodes detected instantaneous per-pixel illumination changes into an asynchronous stream of event packets. Their novelty compared to standard cameras lies in the transition from capturing full picture frames at fixed time intervals to a sparse data format which, with its distinctive qualities, offers potential improvements in various applications. However, these advantages come at the cost of reinventing algorithmic procedures or adapting them to effectively process the new data format. In this survey, we systematically examine neuromorphic vision along three main dimensions. First, we highlight the technological evolution and distinctive hardware features of neuromorphic cameras from their inception to recent models. Second, we review image processing algorithms developed explicitly for event-based data, covering key works on feature detection, tracking, and optical flow -which form the basis for analyzing image elements and transformations -as well as depth and pose estimation or object recognition, which interpret more complex scene structures and components. These techniques, drawn from classical computer vision and modern data-driven approaches, are examined to illustrate the breadth of applications for event-based cameras. Third, we present practical application case studies demonstrating how event cameras have been successfully used across various industries and scenarios. Finally, we analyze the challenges limiting widespread adoption, identify significant research gaps compared to standard imaging techniques, and outline promising future directions and opportunities that neuromorphic vision offers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
