Evaluation of the Intel RealSense T265 for tracking natural human head motion

Abstract

Accurate and robust tracking of natural human head motion in natural environments is important for a number of applications including virtual and augmented reality, clinical diagnostics, as well as basic scientific research. IMU provide a versatile solution for recording inertial data including linear acceleration and angular velocity, but reconstructing head position is difficult or impossible. This problem can be solved by incorporating visual data using a technique known as visual-inertial simultaneous localization and mapping (VI-SLAM). A recently released commercial solution, the Intel RealSense T265, uses a proprietary VI-SLAM algorithm to estimate linear and angular position and velocity, but the performance of this device for tracking of natural human head motion in natural environments has not yet been comprehensively evaluated against gold-standard methods. In this study, we used a wide range of metrics to evaluate the performance of the T265 with different walking speeds in different environments, both indoor and outdoor, against two gold-standard methods, an optical tracking system and a so-called perambulator. Overall, we find that performance of the T265 relative to these gold-standard methods is most accurate for slow to normal walking speeds in small- to medium-sized environments. The suitability of this device for future scientific studies depends on the application; data presented here can be useful in making that determination.

Meaningful Test & Evaluation of Indoor Localization Systems in Semi-Controlled Environments

“…In an experiment presented by Hausamann et al [65], analysis of the absolute position accuracy of the RealSense T265 Tracking Camera based on continuous position data yielded a mean horizontal error of around 0, 4 m. This is in contrast to a mean error of 0, 8 m for application-dependent testing in this work. The data presented by Hausamann et al [65] was gathered by tracking a person on a significantly smaller test area, without the consideration of aisles or alterations of the environment after map recording. Hence, it may be misleading to consider the test and evaluation results for the application 'AGV in warehouse operation'.…”

Meaningful Test and Evaluation of Indoor Localization Systems in Semi-Controlled Environments

“…In an experiment presented by Hausamann et al [ 66 ], analysis of the absolute position accuracy of the RealSense T265 Tracking Camera based on continuous position data yielded a mean horizontal error of around 0.4 m. This is in contrast to a mean error of 0.8 m for application-dependent testing in this work. The data presented by Hausamann et al [ 66 ] were gathered by tracking a person on a significantly smaller test area, without the consideration of aisles or alterations of the environment after map recording. Hence, it may be misleading to consider the test and evaluation results for the application “AGVs in warehouse operation”.…”

Review—Emerging Portable Technologies for Gait Analysis in Neurological Disorders

“…In motion analysis, the system can be used to measure a definite amount of spatiotemporal variables, however, joints with multiple degrees of freedom exhibit inaccuracies yielding difficulties for the forthcoming gait data analysis (Mejia-Trujillo et al, 2019). In general, RealSense seems to perform better at slow to normal walking speeds located in small to mediumsized environments (Hausamann et al, 2021). Auxiliary tools can be used to extend the current three-part system to up to six cameras to improve body shape and joint position tracking (Boppana and Anderson, 2019).…”