{"title":"基于关键点匹配的立体图像车际距离检测","authors":"Y. Shima","doi":"10.1109/CISP-BMEI.2017.8302064","DOIUrl":null,"url":null,"abstract":"An algorithm to detect car distance from a pair of stereo images is presented. It is useful for drivers to avoid collisions and ensure safety to keep the car at a constant distance from the car ahead. The conventional distance detection method is based on image matching; the proposed algorithm is based on key-point matching. Key points are extracted from a stereo image pair by using Speeded Up Robust Features (SURF). The distance is calculated from 3D binocular disparity, the difference of position at the object.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"121 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Inter-vehicle distance detection based on keypoint matching for stereo images\",\"authors\":\"Y. Shima\",\"doi\":\"10.1109/CISP-BMEI.2017.8302064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm to detect car distance from a pair of stereo images is presented. It is useful for drivers to avoid collisions and ensure safety to keep the car at a constant distance from the car ahead. The conventional distance detection method is based on image matching; the proposed algorithm is based on key-point matching. Key points are extracted from a stereo image pair by using Speeded Up Robust Features (SURF). The distance is calculated from 3D binocular disparity, the difference of position at the object.\",\"PeriodicalId\":6474,\"journal\":{\"name\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"121 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI.2017.8302064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2017.8302064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

提出了一种从一对立体图像中检测汽车距离的算法。与前车保持一定的距离对驾驶员避免碰撞和确保安全很有帮助。传统的距离检测方法是基于图像匹配的;该算法基于关键点匹配。利用加速鲁棒特征(SURF)对立体图像进行关键点提取。距离是根据三维双目视差计算的,即物体的位置差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Inter-vehicle distance detection based on keypoint matching for stereo images
An algorithm to detect car distance from a pair of stereo images is presented. It is useful for drivers to avoid collisions and ensure safety to keep the car at a constant distance from the car ahead. The conventional distance detection method is based on image matching; the proposed algorithm is based on key-point matching. Key points are extracted from a stereo image pair by using Speeded Up Robust Features (SURF). The distance is calculated from 3D binocular disparity, the difference of position at the object.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Polarization Characterization and Evaluation of Healing Process of the Damaged-skin Applied with Chitosan and Silicone Hydrogel Applicator Design and Implementation of OpenDayLight Manager Application Extraction of cutting plans in craniosynostosis using convolutional neural networks Evaluation of Flight Test Data Quality Based on Rough Set Theory Radar Emitter Type Identification Effect Based On Different Structural Deep Feedforward Networks
×
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