实时道路车道检测与商品硬件

2014 International Electrical Engineering Congress (iEECON) Pub Date : 2014-03-19 DOI:10.1109/IEECON.2014.7088793

Somchok Sakjiraphong, Andre Pinho, M. Dailey, M. Ekpanyapong, A. Tavares

{"title":"实时道路车道检测与商品硬件","authors":"Somchok Sakjiraphong, Andre Pinho, M. Dailey, M. Ekpanyapong, A. Tavares","doi":"10.1109/IEECON.2014.7088793","DOIUrl":null,"url":null,"abstract":"We present a real-time algorithm for lane boundary estimation based on matched filters and a RANSAC-based method for boundary marking identification. The algorithm is designed to run with minimal assumptions about the environment using a single monocular camera sensor and low-cost commodity compute hardware. With GPU acceleration and TBB, the algorithm runs in less than 25 ms on average on images of size 640 × 480 comparing with 0.12 seconds running on CPU baseline.","PeriodicalId":306512,"journal":{"name":"2014 International Electrical Engineering Congress (iEECON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Real-time road lane detection with commodity hardware\",\"authors\":\"Somchok Sakjiraphong, Andre Pinho, M. Dailey, M. Ekpanyapong, A. Tavares\",\"doi\":\"10.1109/IEECON.2014.7088793\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a real-time algorithm for lane boundary estimation based on matched filters and a RANSAC-based method for boundary marking identification. The algorithm is designed to run with minimal assumptions about the environment using a single monocular camera sensor and low-cost commodity compute hardware. With GPU acceleration and TBB, the algorithm runs in less than 25 ms on average on images of size 640 × 480 comparing with 0.12 seconds running on CPU baseline.\",\"PeriodicalId\":306512,\"journal\":{\"name\":\"2014 International Electrical Engineering Congress (iEECON)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Electrical Engineering Congress (iEECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEECON.2014.7088793\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Electrical Engineering Congress (iEECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEECON.2014.7088793","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

提出了一种基于匹配滤波器的车道边界实时估计算法和一种基于ransac的车道边界标记识别方法。该算法旨在使用单个单目相机传感器和低成本商品计算硬件，在对环境的最小假设下运行。在GPU加速和TBB的情况下，该算法在640 × 480大小的图像上平均运行时间不到25毫秒，而在CPU基线上运行时间为0.12秒。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Real-time road lane detection with commodity hardware

We present a real-time algorithm for lane boundary estimation based on matched filters and a RANSAC-based method for boundary marking identification. The algorithm is designed to run with minimal assumptions about the environment using a single monocular camera sensor and low-cost commodity compute hardware. With GPU acceleration and TBB, the algorithm runs in less than 25 ms on average on images of size 640 × 480 comparing with 0.12 seconds running on CPU baseline.

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

2014 International Electrical Engineering Congress (iEECON)

自引率

0.00%

发文量