Research on Vehicle Parking Position Detection Based on Swin Transformer Semantic Segmentation

Hong-Tu Shi, Jian-Zhang Liu, Ruochao Wang, Yanpeng Huo, Chao-Wei Cui, Yong-qiang Zhang
{"title":"Research on Vehicle Parking Position Detection Based on Swin Transformer Semantic Segmentation","authors":"Hong-Tu Shi, Jian-Zhang Liu, Ruochao Wang, Yanpeng Huo, Chao-Wei Cui, Yong-qiang Zhang","doi":"10.1109/ICSAI57119.2022.10005500","DOIUrl":null,"url":null,"abstract":"Determine whether the vehicle is parked in the specified area, which has high application value in industry, transportation, parking lot, etc. Aiming at the problems of rough results and high maintenance costs, a vehicle parking position detection method based on Swing Transformer semantic segmentation is proposed. The vehicle semantic results obtained by Swin Transformer semantic segmentation algorithm are taken as the main features of vehicles in the picture. Canny algorithm is used to obtain vehicle contour to improve detection accuracy. Calculate the relationship between the vehicle contour and the hand drawn warning line, and compare with the threshold value to determine whether the vehicle is parked in the specified area. Through simulation, industrial application and road application, the method can realize the normative detection of vehicle parking position.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI57119.2022.10005500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Determine whether the vehicle is parked in the specified area, which has high application value in industry, transportation, parking lot, etc. Aiming at the problems of rough results and high maintenance costs, a vehicle parking position detection method based on Swing Transformer semantic segmentation is proposed. The vehicle semantic results obtained by Swin Transformer semantic segmentation algorithm are taken as the main features of vehicles in the picture. Canny algorithm is used to obtain vehicle contour to improve detection accuracy. Calculate the relationship between the vehicle contour and the hand drawn warning line, and compare with the threshold value to determine whether the vehicle is parked in the specified area. Through simulation, industrial application and road application, the method can realize the normative detection of vehicle parking position.
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
基于Swin变压器语义分割的车辆停车位置检测研究
确定车辆是否停在指定区域,在工业、交通、停车场等方面具有很高的应用价值。针对结果粗糙、维护成本高的问题,提出了一种基于Swing Transformer语义分割的车辆停放位置检测方法。将Swin Transformer语义分割算法得到的车辆语义结果作为图像中车辆的主要特征。采用Canny算法获取车辆轮廓,提高检测精度。计算车辆轮廓与手绘警戒线的关系,并与阈值进行比较,判断车辆是否停在指定区域内。通过仿真、工业应用和道路应用,该方法可以实现车辆停放位置的规范检测。
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
Multi-hop Knowledge Base Q&A in Integrated Energy Services Based on Intermediate Reasoning Attention Wrong Wiring Detection of Electricity Meter Based on Image Processing Perturbation Analysis Based Simulation Approach for Electricity Market Research and Investigation Promoting a Hybrid Cryptosystem System’s Security based on Fresnel lens and RSA Algorithm Customer Portrait for Metrology Institutions Based on the Machine Learning Clustering Algorithm and the RFM Model
×
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