从街道全景图像半自动测量街道灯杆的系统

L. Hazelhoff, Ivo M. Creusen, P. D. With
{"title":"从街道全景图像半自动测量街道灯杆的系统","authors":"L. Hazelhoff, Ivo M. Creusen, P. D. With","doi":"10.1109/WACV.2014.6836109","DOIUrl":null,"url":null,"abstract":"Accurate and up-to-date inventories of lighting poles are of interest to energy companies, beneficial for the transition to energy-efficient lighting and may contribute to a more adequate lighting of streets. This potentially improves social security and reduces crime and vandalism during nighttime. This paper describes a system for automated surveying of lighting poles from street-level panoramic images. The system consists of two independent detectors, focusing at the detection of the pole itself and at the detection of a specific lighting fixture type. Both follow the same approach, and start with detection of the feature of interest (pole or fixture) within the individual images, followed by a multi-view analysis to retrieve the real-world coordinates of the poles. Afterwards, the detection output of both algorithms is merged. Large-scale validations, covering about 135 km of road, show that over 91% of the lighting poles is found, while the precision remains above 50%. When applying this system in a semi-automated fashion, high-quality inventories can be created up to 5 times more efficiently compared to manually surveying all poles from the images.","PeriodicalId":73325,"journal":{"name":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","volume":"120 1","pages":"129-136"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"System for semi-automated surveying of street-lighting poles from street-level panoramic images\",\"authors\":\"L. Hazelhoff, Ivo M. Creusen, P. D. With\",\"doi\":\"10.1109/WACV.2014.6836109\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurate and up-to-date inventories of lighting poles are of interest to energy companies, beneficial for the transition to energy-efficient lighting and may contribute to a more adequate lighting of streets. This potentially improves social security and reduces crime and vandalism during nighttime. This paper describes a system for automated surveying of lighting poles from street-level panoramic images. The system consists of two independent detectors, focusing at the detection of the pole itself and at the detection of a specific lighting fixture type. Both follow the same approach, and start with detection of the feature of interest (pole or fixture) within the individual images, followed by a multi-view analysis to retrieve the real-world coordinates of the poles. Afterwards, the detection output of both algorithms is merged. Large-scale validations, covering about 135 km of road, show that over 91% of the lighting poles is found, while the precision remains above 50%. When applying this system in a semi-automated fashion, high-quality inventories can be created up to 5 times more efficiently compared to manually surveying all poles from the images.\",\"PeriodicalId\":73325,\"journal\":{\"name\":\"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision\",\"volume\":\"120 1\",\"pages\":\"129-136\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WACV.2014.6836109\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WACV.2014.6836109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

准确和最新的灯杆库存是能源公司感兴趣的,有利于向节能照明过渡,并可能有助于更充分的街道照明。这可能会改善社会治安,减少夜间的犯罪和破坏行为。本文介绍了一种基于街道全景图像的灯杆自动测量系统。该系统由两个独立的检测器组成,专注于检测电线杆本身和检测特定的照明灯具类型。两者都采用相同的方法,从检测单个图像中的感兴趣的特征(极点或夹具)开始,然后进行多视图分析以检索极点的真实坐标。然后,将两种算法的检测输出进行合并。覆盖约135公里道路的大规模验证表明,超过91%的灯杆被发现,而精度保持在50%以上。当以半自动化的方式应用该系统时,与从图像中手动测量所有极点相比,创建高质量库存的效率可提高5倍。
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
System for semi-automated surveying of street-lighting poles from street-level panoramic images
Accurate and up-to-date inventories of lighting poles are of interest to energy companies, beneficial for the transition to energy-efficient lighting and may contribute to a more adequate lighting of streets. This potentially improves social security and reduces crime and vandalism during nighttime. This paper describes a system for automated surveying of lighting poles from street-level panoramic images. The system consists of two independent detectors, focusing at the detection of the pole itself and at the detection of a specific lighting fixture type. Both follow the same approach, and start with detection of the feature of interest (pole or fixture) within the individual images, followed by a multi-view analysis to retrieve the real-world coordinates of the poles. Afterwards, the detection output of both algorithms is merged. Large-scale validations, covering about 135 km of road, show that over 91% of the lighting poles is found, while the precision remains above 50%. When applying this system in a semi-automated fashion, high-quality inventories can be created up to 5 times more efficiently compared to manually surveying all poles from the images.
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
Ordinal Classification with Distance Regularization for Robust Brain Age Prediction. Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images. PathLDM: Text conditioned Latent Diffusion Model for Histopathology. Domain Generalization with Correlated Style Uncertainty. Semantic-aware Video Representation for Few-shot Action Recognition.
×
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