Realtime Dense Stereo Matching with Dynamic Programming in CUDA

John Congote, Javier Barandiarán, I. Barandiaran, O. Ruiz
{"title":"Realtime Dense Stereo Matching with Dynamic Programming in CUDA","authors":"John Congote, Javier Barandiarán, I. Barandiaran, O. Ruiz","doi":"10.2312/LocalChapterEvents/CEIG/CEIG09/231-234","DOIUrl":null,"url":null,"abstract":"Real-time depth extraction from stereo images is an important process in computer vision. This paper proposes a new implementation of the dynamic programming algorithm to calculate dense depth maps using the CUDA architecture achieving real-time performance with consumer graphics cards. We compare the running time of the algorithm against CPU implementation and demonstrate the scalability property of the algorithm by testing it on different graphics cards.","PeriodicalId":385751,"journal":{"name":"Spanish Computer Graphics Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spanish Computer Graphics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/LocalChapterEvents/CEIG/CEIG09/231-234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

Abstract

Real-time depth extraction from stereo images is an important process in computer vision. This paper proposes a new implementation of the dynamic programming algorithm to calculate dense depth maps using the CUDA architecture achieving real-time performance with consumer graphics cards. We compare the running time of the algorithm against CPU implementation and demonstrate the scalability property of the algorithm by testing it on different graphics cards.
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
基于CUDA动态规划的实时密集立体匹配
立体图像的实时深度提取是计算机视觉中的一个重要过程。本文提出了一种动态规划算法的新实现,该算法使用CUDA架构计算密集深度图,在消费类显卡上实现实时性能。我们比较了该算法与CPU实现的运行时间,并通过在不同显卡上的测试来证明该算法的可扩展性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Noise Reduction Automation of LiDAR Point Clouds for Modeling and Representation of High Voltage Lines in a 3D Virtual Globe On the Design of a Mixed-Reality Annotations Tool for the Inspection of Pre-fab Buildings Extending Industrial Digital Twins with Optical Object Tracking Direct Volume Rendering of Stack-Based Terrains Deployment of Volume Rendering Interactive Visualizations in Web Platforms With Intersected 3D Geometry
×
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