• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用于室内制图应用的 HoloLens 跟踪和深度感应评估。

Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications.

机构信息

Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany.

出版信息

Sensors (Basel). 2020 Feb 14;20(4):1021. doi: 10.3390/s20041021.

DOI:10.3390/s20041021
PMID:32074980
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7070293/
Abstract

The Microsoft HoloLens is a head-worn mobile augmented reality device that is capable of mapping its direct environment in real-time as triangle meshes and localize itself within these three-dimensional meshes simultaneously. The device is equipped with a variety of sensors including four tracking cameras and a time-of-flight (ToF) range camera. Sensor images and their poses estimated by the built-in tracking system can be accessed by the user. This makes the HoloLens potentially interesting as an indoor mapping device. In this paper, we introduce the different sensors of the device and evaluate the complete system in respect of the task of mapping indoor environments. The overall quality of such a system depends mainly on the quality of the depth sensor together with its associated pose derived from the tracking system. For this purpose, we first evaluate the performance of the HoloLens depth sensor and its tracking system separately. Finally, we evaluate the overall system regarding its capability for mapping multi-room environments.

摘要

微软 HoloLens 是一款头戴式移动增强现实设备,能够实时绘制其直接环境的三角形网格,并同时在这些三维网格中定位自身。该设备配备了多种传感器,包括四个跟踪摄像头和一个飞行时间 (ToF) 距离摄像头。用户可以访问内置跟踪系统估计的传感器图像及其姿态。这使得 HoloLens 作为室内测绘设备具有潜在的吸引力。在本文中,我们介绍了该设备的不同传感器,并评估了该系统在室内环境测绘任务方面的整体性能。该系统的整体质量主要取决于深度传感器的质量及其来自跟踪系统的相关姿态。为此,我们首先分别评估 HoloLens 深度传感器及其跟踪系统的性能。最后,我们评估了整个系统在测绘多房间环境方面的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/08cf349b8d74/sensors-20-01021-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/c16649b84268/sensors-20-01021-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/fc54edd003bf/sensors-20-01021-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/963afb86b4fa/sensors-20-01021-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/f60e49f3f5b8/sensors-20-01021-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/4ff87e935d71/sensors-20-01021-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/5b220acaae25/sensors-20-01021-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/d2caf79a7521/sensors-20-01021-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/be03ef0ce58b/sensors-20-01021-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/f302d1672839/sensors-20-01021-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/30df4bd9cd97/sensors-20-01021-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/60db8939e63b/sensors-20-01021-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/518745803432/sensors-20-01021-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/5c9d353aaed1/sensors-20-01021-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/01c4868f9ab2/sensors-20-01021-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/6c7546b665d9/sensors-20-01021-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/ca41c3d17339/sensors-20-01021-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/79b57814206d/sensors-20-01021-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/5361d3a2e4fc/sensors-20-01021-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/a199bcb4406e/sensors-20-01021-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/796f2685303b/sensors-20-01021-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/de1909b04dbc/sensors-20-01021-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/08cf349b8d74/sensors-20-01021-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/c16649b84268/sensors-20-01021-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/fc54edd003bf/sensors-20-01021-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/963afb86b4fa/sensors-20-01021-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/f60e49f3f5b8/sensors-20-01021-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/4ff87e935d71/sensors-20-01021-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/5b220acaae25/sensors-20-01021-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/d2caf79a7521/sensors-20-01021-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/be03ef0ce58b/sensors-20-01021-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/f302d1672839/sensors-20-01021-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/30df4bd9cd97/sensors-20-01021-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/60db8939e63b/sensors-20-01021-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/518745803432/sensors-20-01021-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/5c9d353aaed1/sensors-20-01021-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/01c4868f9ab2/sensors-20-01021-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/6c7546b665d9/sensors-20-01021-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/ca41c3d17339/sensors-20-01021-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/79b57814206d/sensors-20-01021-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/5361d3a2e4fc/sensors-20-01021-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/a199bcb4406e/sensors-20-01021-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/796f2685303b/sensors-20-01021-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/de1909b04dbc/sensors-20-01021-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb45/7070293/08cf349b8d74/sensors-20-01021-g022.jpg

相似文献

1
Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications.用于室内制图应用的 HoloLens 跟踪和深度感应评估。
Sensors (Basel). 2020 Feb 14;20(4):1021. doi: 10.3390/s20041021.
2
Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro.使用娱乐设备进行室内映射:评估针对微软HoloLens 2和苹果iPhone 14 Pro的不同映射策略的影响。
Sensors (Basel). 2024 Feb 6;24(4):1062. doi: 10.3390/s24041062.
3
HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments.HyMoTrack:一种用于复杂室内环境的移动增强现实导航系统。
Sensors (Basel). 2015 Dec 24;16(1):17. doi: 10.3390/s16010017.
4
Augmented Reality Technology Using Microsoft HoloLens in Anatomic Pathology.使用 Microsoft HoloLens 的增强现实技术在解剖病理学中的应用。
Arch Pathol Lab Med. 2018 May;142(5):638-644. doi: 10.5858/arpa.2017-0189-OA. Epub 2018 Jan 31.
5
HoloLens-Based Vascular Localization System: Precision Evaluation Study With a Three-Dimensional Printed Model.基于HoloLens的血管定位系统:三维打印模型的精度评估研究
J Med Internet Res. 2020 Apr 17;22(4):e16852. doi: 10.2196/16852.
6
Three-dimensional cameras and skeleton pose tracking for physical function assessment: A review of uses, validity, current developments and Kinect alternatives.用于身体功能评估的三维相机和骨骼姿势跟踪:用途、有效性、当前进展及Kinect替代方案综述
Gait Posture. 2019 Feb;68:193-200. doi: 10.1016/j.gaitpost.2018.11.029. Epub 2018 Nov 22.
7
Towards Kilo-Hertz 6-DoF Visual Tracking Using an Egocentric Cluster of Rolling Shutter Cameras.利用以自我为中心的滚动快门相机集群实现千赫兹6自由度视觉跟踪
IEEE Trans Vis Comput Graph. 2016 Nov;22(11):2358-67. doi: 10.1109/TVCG.2016.2593757. Epub 2016 Jul 27.
8
Augmenting Microsoft's HoloLens with vuforia tracking for neuronavigation.通过Vuforia跟踪增强微软HoloLens用于神经导航。
Healthc Technol Lett. 2018 Oct 4;5(5):221-225. doi: 10.1049/htl.2018.5079. eCollection 2018 Oct.
9
UltrARsound: in situ visualization of live ultrasound images using HoloLens 2.超声 AR:使用 HoloLens 2 实现实时超声图像的现场可视化。
Int J Comput Assist Radiol Surg. 2022 Nov;17(11):2081-2091. doi: 10.1007/s11548-022-02695-z. Epub 2022 Jul 1.
10
Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling.用于详细3D室内和室外建模的增强型RGB-D映射方法
Sensors (Basel). 2016 Sep 27;16(10):1589. doi: 10.3390/s16101589.

引用本文的文献

1
Evaluating Augmented Reality Head-Mounted Devices in Healthcare: A Review of Hardware, Software, and Usability Approaches.评估医疗保健领域的增强现实头戴式设备:硬件、软件及可用性方法综述
Med Devices (Auckl). 2025 Aug 22;18:427-445. doi: 10.2147/MDER.S541187. eCollection 2025.
2
Smart Safety Helmets with Integrated Vision Systems for Industrial Infrastructure Inspection: A Comprehensive Review of VSLAM-Enabled Technologies.用于工业基础设施检测的集成视觉系统智能安全帽:对基于视觉同步定位与地图构建(VSLAM)技术的全面综述
Sensors (Basel). 2025 Aug 6;25(15):4834. doi: 10.3390/s25154834.
3
Evaluation of augmented reality guidance for glenoid pin placement in total shoulder arthroplasty.

本文引用的文献

1
The Accuracy Comparison of Three Simultaneous Localization and Mapping (SLAM)-Based Indoor Mapping Technologies.三种基于同时定位与地图构建(SLAM)的室内地图构建技术的准确性比较。
Sensors (Basel). 2018 Sep 25;18(10):3228. doi: 10.3390/s18103228.
2
Behavior Analysis of Novel Wearable Indoor Mapping System Based on 3D-SLAM.基于3D-SLAM的新型可穿戴室内地图系统的行为分析
Sensors (Basel). 2018 Mar 2;18(3):766. doi: 10.3390/s18030766.
3
Virtually Nursing: Emerging Technologies in Nursing Education.虚拟护理:护理教育中的新兴技术。
全肩关节置换术中用于肩胛盂钢针置入的增强现实引导技术评估
Int J Comput Assist Radiol Surg. 2025 Jun 11. doi: 10.1007/s11548-025-03444-8.
4
HoloLens platform for healthcare professionals simulation training, teaching, and its urological applications: an up-to-date review.用于医疗专业人员模拟培训、教学及其泌尿外科应用的HoloLens平台:最新综述
Ther Adv Urol. 2024 Dec 8;16:17562872241297554. doi: 10.1177/17562872241297554. eCollection 2024 Jan-Dec.
5
Augmented reality for point-of-care ultrasound-guided vascular access in pediatric patients using Microsoft HoloLens 2: a preliminary evaluation.使用微软HoloLens 2的增强现实技术在儿科患者床旁超声引导下进行血管穿刺:一项初步评估。
J Med Imaging (Bellingham). 2024 Nov;11(6):062604. doi: 10.1117/1.JMI.11.6.062604. Epub 2024 Sep 13.
6
Depth-Sensing-Based Algorithm for Chest Morphology Assessment in Children with Cerebral Palsy.基于深度感知的脑瘫儿童胸廓形态评估算法。
Sensors (Basel). 2024 Aug 28;24(17):5575. doi: 10.3390/s24175575.
7
Real-Time Spatial Mapping in Architectural Visualization: A Comparison among Mixed Reality Devices.建筑可视化中的实时空间映射:混合现实设备之间的比较
Sensors (Basel). 2024 Jul 21;24(14):4727. doi: 10.3390/s24144727.
8
A Fast and Interactive Augmented Reality System for PET/CT-guided Intervention of Neuroblastoma.一种用于神经母细胞瘤PET/CT引导介入的快速交互式增强现实系统。
Proc SPIE Int Soc Opt Eng. 2024 Feb;12928. doi: 10.1117/12.3008663. Epub 2024 Mar 29.
9
Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro.使用娱乐设备进行室内映射:评估针对微软HoloLens 2和苹果iPhone 14 Pro的不同映射策略的影响。
Sensors (Basel). 2024 Feb 6;24(4):1062. doi: 10.3390/s24041062.
10
Combined Filtering Method for Offshore Oil and Gas Platform Point Cloud Data Based on KNN_PCF and Hy_WHF and Its Application in 3D Reconstruction.基于KNN_PCF和Hy_WHF的海洋油气平台点云数据联合滤波方法及其在三维重建中的应用
Sensors (Basel). 2024 Jan 18;24(2):615. doi: 10.3390/s24020615.
Nurse Educ. 2017 Jan/Feb;42(1):14-17. doi: 10.1097/NNE.0000000000000295.
4
Accuracy and resolution of Kinect depth data for indoor mapping applications.用于室内制图应用的 Kinect 深度数据的准确性和分辨率。
Sensors (Basel). 2012;12(2):1437-54. doi: 10.3390/s120201437. Epub 2012 Feb 1.