摘要
事件相机是模仿生物视网膜的成像方式,具有高动态、低延迟、高时间分辨率以及低功耗的特性。其突破传统相机难以捕捉在高动态范围情况下的物体并进行目标识别的困境,事件相机的特性对于研究基于事件相机的目标检测问题具有实验意义。简要叙述事件相机的现状、发展过程、优势与挑战,介绍了各种类型事件相机的工作原理和一些基于事件相机的目标检测算法,阐述了基于事件相机的目标检测算法面对的挑战和未来趋势,并进行了总结。
Event cameras are imaging methods that mimic biological retinas,with high dynamics,low latency,high temporal resolution and low power consumption.It breaks through the dilemma that traditional cameras are difficult to capture objects and target recognition under high dynamic range,and the characteristics of event cameras are of experimental significance for studying the object detection problem based on event cameras.This paper first briefly describes the status,development process,advantages and challenges of event cameras,then introduces the working principle of various types of event cameras and some object detection algorithms based on event cameras,and finally explains the challenges and future trends of object detection algorithms based on event cameras,and summarizes the article.
作者
张亚丽
田启川
唐超林
ZHANG Yali;TIAN Qichuan;TANG Chaolin(School of Electrical and Information Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Key Laboratory of Intelligent Processing for Building Big Data,Beijing 100044,China)
出处
《计算机工程与应用》
CSCD
北大核心
2024年第13期23-35,共13页
Computer Engineering and Applications
基金
北京建筑大学2023年度研究生创新项目(07081023002)。
关键词
事件相机
目标检测
神经网络
event cameras
object detection
neural networks