河南理工大学学报（自然科学版）2025，Vol.44Issue(5)：17-26,10.DOI:10.16186/j.cnki.1673-9787.2024070033
将异步事件流转换为网格表示的方法研究
Study on the method of converting asynchronous event stream into grid representation
摘要
Abstract
Objectives To address the complexity and sparsity of asynchronous event streams,which compli-cate data analysis,reduce storage and computational efficiency,a method was proposed to convert asyn-chronous event stream into grid representation.Methods Each event was replaced by a Dirac delta function and represented as a set of event fields.Based on tensor characteristics,average measurements were as-signed to events missing the same category of information,reducing computation while preserving high dy-namic resolution.Usable data were selected,and a multilayer perceptron(MLP)was used to replace manu-ally chosen aggregation kernels to identify optimal measurement functions.In ECTResNet,convolution was performed and dimension was reduced through periodic sampling to retain key information for quantization.The convolved data were discretized in continuous 3D space to generate a fixed-size grid.Finally,the event stream was transformed into a grid representation suitable for deep learning.Results The proposed method was evaluated on the N-Cars and N-Caltech101 datasets.Recognition accuracies reached 97.07%and 87.72%,respectively,improving by 10.09%and 11.44%over the event spike tensor method.Conclusions Ex-periments showed that converting asynchronous event stream into grid representation enhanced compatibility with deep learning models,improved accuracy and efficiency of event processing and recognition,and en-abled end-to-end representation learning.This approach held broad potential in sensor data processing and event recognition.关键词
事件相机/异步事件流/深度学习/卷积神经网络Key words
event camera/asynchronous event stream/deep learning/convolutional neural network分类
信息技术与安全科学引用本文复制引用
王妍玮,张佳宇,陈凯云,任春平..将异步事件流转换为网格表示的方法研究[J].河南理工大学学报（自然科学版）,2025,44(5):17-26,10.基金项目
国家自然科学基金资助项目(52204131) （52204131）
黑龙江省重点研发计划战略研究专项项目(GA23A910) （GA23A910）
黑龙江省科研基本业务费项目(2022-KYYWF-0527) （2022-KYYWF-0527）
