{"title":"A novel stereo camera based collision warning system for automotive applications","authors":"Adrian Leu, D. Aiteanu, A. Gräser","doi":"10.1109/SACI.2011.5873038","DOIUrl":null,"url":null,"abstract":"In collision warning systems for automotive applications the response time of a system is very important, since a precise response is useless if it comes too late. In this paper a fast collision warning system is presented, which uses a stereo camera as a sensor. The used algorithms allow a fast response of the system by making use of parallel processing. The parallel processing algorithms have been implemented and tested using an Nvidia Tesla C1060 GPU, programmed using the Nvidia CUDA API. The processing time comparison between the CPU based and optimized GPU based versions of the algorithms are also presented.","PeriodicalId":334381,"journal":{"name":"2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2011.5873038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
In collision warning systems for automotive applications the response time of a system is very important, since a precise response is useless if it comes too late. In this paper a fast collision warning system is presented, which uses a stereo camera as a sensor. The used algorithms allow a fast response of the system by making use of parallel processing. The parallel processing algorithms have been implemented and tested using an Nvidia Tesla C1060 GPU, programmed using the Nvidia CUDA API. The processing time comparison between the CPU based and optimized GPU based versions of the algorithms are also presented.
在汽车碰撞预警系统中,系统的响应时间非常重要,因为如果来得太晚,精确的响应将是无用的。本文提出了一种以立体摄像机为传感器的快速碰撞预警系统。所使用的算法通过使用并行处理来允许系统的快速响应。并行处理算法已经在Nvidia Tesla C1060 GPU上实现和测试,使用Nvidia CUDA API编程。并比较了基于CPU和优化后的GPU两种算法的处理时间。