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用于动态六自由度测量的非重叠视场多相机标定架。

A Multi-Camera Rig with Non-Overlapping Views for Dynamic Six-Degree-of-Freedom Measurement.

机构信息

State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China.

出版信息

Sensors (Basel). 2019 Jan 10;19(2):250. doi: 10.3390/s19020250.

DOI:10.3390/s19020250
PMID:30634653
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6358974/
Abstract

Large-scale measurement plays an increasingly important role in intelligent manufacturing. However, existing instruments have problems with immersive experiences. In this paper, an immersive positioning and measuring method based on augmented reality is introduced. An inside-out vision measurement approach using a multi-camera rig with non-overlapping views is presented for dynamic six-degree-of-freedom measurement. By using active LED markers, a flexible and robust solution is delivered to deal with complex manufacturing sites. The space resection adjustment principle is addressed and measurement errors are simulated. The improved Nearest Neighbor method is employed for feature correspondence. The proposed tracking method is verified by experiments and results with good performance are obtained.

摘要

大规模测量在智能制造中起着越来越重要的作用。然而,现有的仪器在沉浸式体验方面存在问题。本文提出了一种基于增强现实的沉浸式定位和测量方法。提出了一种使用多相机架和非重叠视图的内部视觉测量方法,用于动态六自由度测量。通过使用主动 LED 标记,提供了一种灵活且强大的解决方案,以应对复杂的制造现场。解决了空间前方交会调整原理和测量误差的模拟问题。采用改进的最近邻方法进行特征对应。通过实验验证了所提出的跟踪方法,并得到了性能良好的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/53fe8f74ff0e/sensors-19-00250-g019.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/cb615349da5f/sensors-19-00250-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/2487b399a8e6/sensors-19-00250-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/db7222ad9a96/sensors-19-00250-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/455d14aa61be/sensors-19-00250-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/2f671e268507/sensors-19-00250-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/53fe8f74ff0e/sensors-19-00250-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/6128094f2acc/sensors-19-00250-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/ffe6f5292ec6/sensors-19-00250-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/630a148f2e63/sensors-19-00250-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/cb615349da5f/sensors-19-00250-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/2487b399a8e6/sensors-19-00250-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/712c6505b654/sensors-19-00250-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/a7cbecdb35e0/sensors-19-00250-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/db7222ad9a96/sensors-19-00250-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/455d14aa61be/sensors-19-00250-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/2f671e268507/sensors-19-00250-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4259/6358974/53fe8f74ff0e/sensors-19-00250-g019.jpg

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Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion.使用自适应视觉惯性融合的移动增强/虚拟现实实时运动跟踪
Sensors (Basel). 2017 May 5;17(5):1037. doi: 10.3390/s17051037.