Evaluation of Embedded Devices for Real- Time Video Lane Detection

K. Podbucki, J. Suder, T. Marciniak, A. Dabrowski
{"title":"Evaluation of Embedded Devices for Real- Time Video Lane Detection","authors":"K. Podbucki, J. Suder, T. Marciniak, A. Dabrowski","doi":"10.23919/mixdes55591.2022.9838167","DOIUrl":null,"url":null,"abstract":"This paper presents a comparison of the performance of embedded systems processing video sequences in real time. As part of the work, practical programs for detecting lanes located on airport areas, which allow autonomous vehicles to move around the airport, were tested. The following modules were used during the tests: Raspberry Pi 4B, NVIDIA Jetson Nano, NVIDIA Jetson Xavier AGX. For modules from the NVIDIA Jetson family, the maximum performance of video stream processing depending on the resolution and the selected power mode has been checked. The results of the experiment show that NVIDIA Jetson modules have sufficient computing resources to effectively track lines based on the camera image, even in low power modes.","PeriodicalId":356244,"journal":{"name":"2022 29th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 29th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/mixdes55591.2022.9838167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

This paper presents a comparison of the performance of embedded systems processing video sequences in real time. As part of the work, practical programs for detecting lanes located on airport areas, which allow autonomous vehicles to move around the airport, were tested. The following modules were used during the tests: Raspberry Pi 4B, NVIDIA Jetson Nano, NVIDIA Jetson Xavier AGX. For modules from the NVIDIA Jetson family, the maximum performance of video stream processing depending on the resolution and the selected power mode has been checked. The results of the experiment show that NVIDIA Jetson modules have sufficient computing resources to effectively track lines based on the camera image, even in low power modes.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
实时视频车道检测的嵌入式设备评价
本文对嵌入式系统实时处理视频序列的性能进行了比较。作为工作的一部分,测试了用于检测机场区域车道的实用程序,这些车道允许自动驾驶汽车在机场周围移动。在测试中使用了以下模块:树莓派4B, NVIDIA Jetson Nano, NVIDIA Jetson Xavier AGX。对于NVIDIA Jetson系列的模块,视频流处理的最大性能取决于分辨率和所选的电源模式已被检查。实验结果表明,即使在低功耗模式下,NVIDIA Jetson模块也具有足够的计算资源,可以根据相机图像有效地跟踪线条。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Analysis of Photovoltaics Performance Under Variable Conditions Design of 1.55 NEF, 2µA, Chopper Based Amplifier in 40nm CMOS for Biomedical Multichannel Integrated System Adaptive Resonance Control Dased on the ANC-VSS-LMS Algorithm for Microphonics Compensation IC Masks - The Challenges of the Newest Technologies Observation of Readout Temperature Dependence and Its Variability for the MEMS and ASIC System Specimens and Their PCB Testbenches
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1