基于视觉的行人检测:保护者系统

D. Gavrila, J. Giebel, S. Munder
{"title":"基于视觉的行人检测:保护者系统","authors":"D. Gavrila, J. Giebel, S. Munder","doi":"10.1109/IVS.2004.1336348","DOIUrl":null,"url":null,"abstract":"This paper presents the results of the first large-scale field tests on vision-based pedestrian protection from a moving vehicle. Our PROTECTOR system combines pedestrian detection, trajectory estimation, risk assessment and driver warning. The paper pursues a \"system approach\" related to the detection component. An optimization scheme models the system as a succession of individual modules and finds a good overall parameter setting by combining individual ROCs using a convex-hull technique. On the experimental side, we present a methodology for the validation of the pedestrian detection performance in an actual vehicle setting. We hope this test methodology to contribute towards the establishment of benchmark testing, enabling this application to mature. We validate the PROTECTOR system using the proposed methodology and present interesting quantitative results based on tens of thousands of images from hours of driving. Although results are promising, more research is needed before such systems can be placed at the hands of ordinary vehicle drivers.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"263","resultStr":"{\"title\":\"Vision-based pedestrian detection: the PROTECTOR system\",\"authors\":\"D. Gavrila, J. Giebel, S. Munder\",\"doi\":\"10.1109/IVS.2004.1336348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the results of the first large-scale field tests on vision-based pedestrian protection from a moving vehicle. Our PROTECTOR system combines pedestrian detection, trajectory estimation, risk assessment and driver warning. The paper pursues a \\\"system approach\\\" related to the detection component. An optimization scheme models the system as a succession of individual modules and finds a good overall parameter setting by combining individual ROCs using a convex-hull technique. On the experimental side, we present a methodology for the validation of the pedestrian detection performance in an actual vehicle setting. We hope this test methodology to contribute towards the establishment of benchmark testing, enabling this application to mature. We validate the PROTECTOR system using the proposed methodology and present interesting quantitative results based on tens of thousands of images from hours of driving. Although results are promising, more research is needed before such systems can be placed at the hands of ordinary vehicle drivers.\",\"PeriodicalId\":296386,\"journal\":{\"name\":\"IEEE Intelligent Vehicles Symposium, 2004\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"263\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Intelligent Vehicles Symposium, 2004\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2004.1336348\",\"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 Intelligent Vehicles Symposium, 2004","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2004.1336348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 263

摘要

本文介绍了基于视觉保护行人免受移动车辆伤害的首次大规模现场测试结果。我们的保护者系统结合了行人检测、轨迹估计、风险评估和驾驶员警告。本文采用与检测组件相关的“系统方法”。优化方案将系统建模为一系列独立模块,并通过使用凸壳技术将各个roc组合在一起,找到一个良好的总体参数设置。在实验方面,我们提出了一种在实际车辆设置中验证行人检测性能的方法。我们希望这种测试方法有助于建立基准测试,使该应用程序成熟。我们使用提出的方法验证了保护者系统,并根据数万张驾驶时间的图像给出了有趣的定量结果。虽然结果很有希望,但在将这种系统应用于普通车辆驾驶员手中之前,还需要进行更多的研究。
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
Vision-based pedestrian detection: the PROTECTOR system
This paper presents the results of the first large-scale field tests on vision-based pedestrian protection from a moving vehicle. Our PROTECTOR system combines pedestrian detection, trajectory estimation, risk assessment and driver warning. The paper pursues a "system approach" related to the detection component. An optimization scheme models the system as a succession of individual modules and finds a good overall parameter setting by combining individual ROCs using a convex-hull technique. On the experimental side, we present a methodology for the validation of the pedestrian detection performance in an actual vehicle setting. We hope this test methodology to contribute towards the establishment of benchmark testing, enabling this application to mature. We validate the PROTECTOR system using the proposed methodology and present interesting quantitative results based on tens of thousands of images from hours of driving. Although results are promising, more research is needed before such systems can be placed at the hands of ordinary vehicle drivers.
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
Design of an instrumented vehicle test bed for developing a human centered driver support system Defect detection on rail surfaces by a vision based system Probabilistic contour extraction with model-switching for vehicle localization A fuzzy ranking method for automated highway driving Fusion of range and vision for real-time motion estimation
×
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