基于FPGA的高分辨率主动立体视觉

Marc Pfeifer, P. Scholl, R. Voigt, B. Becker
{"title":"基于FPGA的高分辨率主动立体视觉","authors":"Marc Pfeifer, P. Scholl, R. Voigt, B. Becker","doi":"10.1109/FCCM.2019.00026","DOIUrl":null,"url":null,"abstract":"We present a novel FPGA based active stereo vision system, tailored for the use in a mobile 3D stereo camera. For the generation of a single 3D map the matching algorithm is based on a correlation approach, where multiple stereo image pairs instead of a single one are processed to guarantee an improved depth resolution. To efficiently handle the large amounts of incoming image data we adapt the algorithm to the underlying FPGA structures, e.g. by making use of pipelining and parallelization.Experiments demonstrate that our approach provides high-quality 3D maps at least three times more energy-efficient (5.5 fps/W) than comparable approaches executed on CPU and GPU platforms. Implemented on a Xilinx Zynq-7030 SoC our system provides a computation speed of 12.2 fps, at a resolution of 1.3 megapixel and a 128 pixel disparity search space. As such it outperforms the currently best passive stereo systems of the Middlebury Stereo Evaluation in terms of speed and accuracy. The presented approach is therefore well suited for mobile applications, that require a highly accurate and energy-efficient active stereo vision system.","PeriodicalId":116955,"journal":{"name":"2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Active Stereo Vision with High Resolution on an FPGA\",\"authors\":\"Marc Pfeifer, P. Scholl, R. Voigt, B. Becker\",\"doi\":\"10.1109/FCCM.2019.00026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a novel FPGA based active stereo vision system, tailored for the use in a mobile 3D stereo camera. For the generation of a single 3D map the matching algorithm is based on a correlation approach, where multiple stereo image pairs instead of a single one are processed to guarantee an improved depth resolution. To efficiently handle the large amounts of incoming image data we adapt the algorithm to the underlying FPGA structures, e.g. by making use of pipelining and parallelization.Experiments demonstrate that our approach provides high-quality 3D maps at least three times more energy-efficient (5.5 fps/W) than comparable approaches executed on CPU and GPU platforms. Implemented on a Xilinx Zynq-7030 SoC our system provides a computation speed of 12.2 fps, at a resolution of 1.3 megapixel and a 128 pixel disparity search space. As such it outperforms the currently best passive stereo systems of the Middlebury Stereo Evaluation in terms of speed and accuracy. The presented approach is therefore well suited for mobile applications, that require a highly accurate and energy-efficient active stereo vision system.\",\"PeriodicalId\":116955,\"journal\":{\"name\":\"2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FCCM.2019.00026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2019.00026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

我们提出了一种新颖的基于FPGA的主动立体视觉系统,专门用于移动3D立体相机。对于单张三维地图的生成,匹配算法基于相关方法,其中处理多个立体图像对而不是单个立体图像对以保证提高深度分辨率。为了有效地处理大量传入的图像数据,我们使算法适应底层FPGA结构,例如利用流水线和并行化。实验表明,我们的方法提供的高质量3D地图的能效至少是在CPU和GPU平台上执行的类似方法的三倍(5.5 fps/W)。我们的系统在Xilinx Zynq-7030 SoC上实现,在130万像素的分辨率和128像素的视差搜索空间下提供12.2 fps的计算速度。因此,它优于目前最好的被动立体系统的米德尔伯里立体评估在速度和准确性方面。因此,所提出的方法非常适合移动应用,这需要一个高度精确和节能的主动立体视觉系统。
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
Active Stereo Vision with High Resolution on an FPGA
We present a novel FPGA based active stereo vision system, tailored for the use in a mobile 3D stereo camera. For the generation of a single 3D map the matching algorithm is based on a correlation approach, where multiple stereo image pairs instead of a single one are processed to guarantee an improved depth resolution. To efficiently handle the large amounts of incoming image data we adapt the algorithm to the underlying FPGA structures, e.g. by making use of pipelining and parallelization.Experiments demonstrate that our approach provides high-quality 3D maps at least three times more energy-efficient (5.5 fps/W) than comparable approaches executed on CPU and GPU platforms. Implemented on a Xilinx Zynq-7030 SoC our system provides a computation speed of 12.2 fps, at a resolution of 1.3 megapixel and a 128 pixel disparity search space. As such it outperforms the currently best passive stereo systems of the Middlebury Stereo Evaluation in terms of speed and accuracy. The presented approach is therefore well suited for mobile applications, that require a highly accurate and energy-efficient active stereo vision system.
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
Hardware Acceleration of Long Read Pairwise Overlapping in Genome Sequencing: A Race Between FPGA and GPU MEG: A RISCV-Based System Simulation Infrastructure for Exploring Memory Optimization Using FPGAs and Hybrid Memory Cube π-BA: Bundle Adjustment Acceleration on Embedded FPGAs with Co-observation Optimization Safe Task Interruption for FPGAs Analyzing the Energy-Efficiency of Vision Kernels on Embedded CPU, GPU and FPGA Platforms
×
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