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一种用于确定深度相机在人体地标定位估计中准确性的简单基准测试方法:以静态直立姿势作为测量示例。

Simple benchmarking method for determining the accuracy of depth cameras in body landmark location estimation: Static upright posture as a measurement example.

机构信息

Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan.

Washington State Department of Labor and Industries, Olympia, Washington, United States of America.

出版信息

PLoS One. 2021 Jul 21;16(7):e0254814. doi: 10.1371/journal.pone.0254814. eCollection 2021.

Abstract

To evaluate the postures in ergonomics applications, studies have proposed the use of low-cost, marker-less, and portable depth camera-based motion tracking systems (DCMTSs) as a potential alternative to conventional marker-based motion tracking systems (MMTSs). However, a simple but systematic method for examining the estimation errors of various DCMTSs is lacking. This paper proposes a benchmarking method for assessing the estimation accuracy of depth cameras for full-body landmark location estimation. A novel alignment board was fabricated to align the coordinate systems of the DCMTSs and MMTSs. The data from an MMTS were used as a reference to quantify the error of using a DCMTS to identify target locations in a 3-D space. To demonstrate the proposed method, the full-body landmark location tracking errors were evaluated for a static upright posture using two different DCMTSs. For each landmark, we compared each DCMTS (Kinect system and RealSense system) with an MMTS by calculating the Euclidean distances between symmetrical landmarks. The evaluation trials were performed twice. The agreement between the tracking errors of the two evaluation trials was assessed using intraclass correlation coefficient (ICC). The results indicate that the proposed method can effectively assess the tracking performance of DCMTSs. The average errors (standard deviation) for the Kinect system and RealSense system were 2.80 (1.03) cm and 5.14 (1.49) cm, respectively. The highest average error values were observed in the depth orientation for both DCMTSs. The proposed method achieved high reliability with ICCs of 0.97 and 0.92 for the Kinect system and RealSense system, respectively.

摘要

为了在人体工程学应用中评估姿势,研究提出使用低成本、无标记和便携式基于深度相机的运动跟踪系统(DCMTS)作为传统基于标记的运动跟踪系统(MMTS)的潜在替代方案。然而,缺乏一种简单但系统的方法来检查各种 DCMTS 的估计误差。本文提出了一种用于评估用于全身地标位置估计的深度相机估计准确性的基准测试方法。制作了一个新颖的对准板,以对准 DCMTS 和 MMTS 的坐标系。使用 MMTS 的数据作为参考,以量化使用 DCMTS 在 3D 空间中识别目标位置的误差。为了演示所提出的方法,使用两种不同的 DCMTS 评估了静态直立姿势的全身地标位置跟踪误差。对于每个地标,我们通过计算对称地标之间的欧几里得距离,将每个 DCMTS(Kinect 系统和 RealSense 系统)与 MMTS 进行比较。评估试验进行了两次。使用组内相关系数(ICC)评估两次评估试验的跟踪误差之间的一致性。结果表明,所提出的方法可以有效地评估 DCMTS 的跟踪性能。Kinect 系统和 RealSense 系统的平均误差(标准偏差)分别为 2.80(1.03)cm 和 5.14(1.49)cm。对于这两个 DCMTS,在深度方向上观察到的平均误差值最高。对于 Kinect 系统和 RealSense 系统,所提出的方法分别达到了 0.97 和 0.92 的高可靠性 ICC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/8294549/45e4af8c097f/pone.0254814.g001.jpg

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