使用多个自主微型飞行器的无标记户外人体动作捕捉

Nitin Saini, E. Price, Rahul Tallamraju, R. Enficiaud, R. Ludwig, Igor Martinovic, Aamir Ahmad, Michael J. Black
{"title":"使用多个自主微型飞行器的无标记户外人体动作捕捉","authors":"Nitin Saini, E. Price, Rahul Tallamraju, R. Enficiaud, R. Ludwig, Igor Martinovic, Aamir Ahmad, Michael J. Black","doi":"10.1109/ICCV.2019.00091","DOIUrl":null,"url":null,"abstract":"Capturing human motion in natural scenarios means moving motion capture out of the lab and into the wild. Typical approaches rely on fixed, calibrated, cameras and reflective markers on the body, significantly limiting the motions that can be captured. To make motion capture truly unconstrained, we describe the first fully autonomous outdoor capture system based on flying vehicles. We use multiple micro-aerial-vehicles(MAVs), each equipped with a monocular RGB camera, an IMU, and a GPS receiver module. These detect the person, optimize their position, and localize themselves approximately. We then develop a markerless motion capture method that is suitable for this challenging scenario with a distant subject, viewed from above, with approximately calibrated and moving cameras. We combine multiple state-of-the-art 2D joint detectors with a 3D human body model and a powerful prior on human pose. We jointly optimize for 3D body pose and camera pose to robustly fit the 2D measurements. To our knowledge, this is the first successful demonstration of outdoor, full-body, markerless motion capture from autonomous flying vehicles.","PeriodicalId":6728,"journal":{"name":"2019 IEEE/CVF International Conference on Computer Vision (ICCV)","volume":"26 1","pages":"823-832"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Markerless Outdoor Human Motion Capture Using Multiple Autonomous Micro Aerial Vehicles\",\"authors\":\"Nitin Saini, E. Price, Rahul Tallamraju, R. Enficiaud, R. Ludwig, Igor Martinovic, Aamir Ahmad, Michael J. Black\",\"doi\":\"10.1109/ICCV.2019.00091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Capturing human motion in natural scenarios means moving motion capture out of the lab and into the wild. Typical approaches rely on fixed, calibrated, cameras and reflective markers on the body, significantly limiting the motions that can be captured. To make motion capture truly unconstrained, we describe the first fully autonomous outdoor capture system based on flying vehicles. We use multiple micro-aerial-vehicles(MAVs), each equipped with a monocular RGB camera, an IMU, and a GPS receiver module. These detect the person, optimize their position, and localize themselves approximately. We then develop a markerless motion capture method that is suitable for this challenging scenario with a distant subject, viewed from above, with approximately calibrated and moving cameras. We combine multiple state-of-the-art 2D joint detectors with a 3D human body model and a powerful prior on human pose. We jointly optimize for 3D body pose and camera pose to robustly fit the 2D measurements. To our knowledge, this is the first successful demonstration of outdoor, full-body, markerless motion capture from autonomous flying vehicles.\",\"PeriodicalId\":6728,\"journal\":{\"name\":\"2019 IEEE/CVF International Conference on Computer Vision (ICCV)\",\"volume\":\"26 1\",\"pages\":\"823-832\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/CVF International Conference on Computer Vision (ICCV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.2019.00091\",\"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/CVF International Conference on Computer Vision (ICCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2019.00091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30

摘要

在自然场景中捕捉人类动作意味着将动作捕捉从实验室搬到野外。典型的方法依赖于固定的、校准的相机和身体上的反射标记,这极大地限制了可以捕捉到的动作。为了使动作捕捉真正不受约束,我们描述了第一个基于飞行器的全自动户外捕捉系统。我们使用多个微型飞行器(MAVs),每个都配备了一个单目RGB相机,一个IMU和一个GPS接收器模块。它们检测人,优化他们的位置,并大致定位自己。然后,我们开发了一种无标记运动捕捉方法,适用于这种具有挑战性的场景,从上面看远处的主体,使用大约校准和移动的相机。我们将多个最先进的2D关节探测器与3D人体模型和强大的人体姿势先验相结合。我们共同优化了三维身体姿态和相机姿态,以鲁棒拟合二维测量值。据我们所知,这是第一次成功展示户外,全身,无标记的动作捕捉自动飞行车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Markerless Outdoor Human Motion Capture Using Multiple Autonomous Micro Aerial Vehicles
Capturing human motion in natural scenarios means moving motion capture out of the lab and into the wild. Typical approaches rely on fixed, calibrated, cameras and reflective markers on the body, significantly limiting the motions that can be captured. To make motion capture truly unconstrained, we describe the first fully autonomous outdoor capture system based on flying vehicles. We use multiple micro-aerial-vehicles(MAVs), each equipped with a monocular RGB camera, an IMU, and a GPS receiver module. These detect the person, optimize their position, and localize themselves approximately. We then develop a markerless motion capture method that is suitable for this challenging scenario with a distant subject, viewed from above, with approximately calibrated and moving cameras. We combine multiple state-of-the-art 2D joint detectors with a 3D human body model and a powerful prior on human pose. We jointly optimize for 3D body pose and camera pose to robustly fit the 2D measurements. To our knowledge, this is the first successful demonstration of outdoor, full-body, markerless motion capture from autonomous flying vehicles.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信