HTC Vive Tracker: Accuracy for Indoor Localization

Lwowski, Jonathan; Majumdat, Abhijit; Benavidez, Patrick; Prevost, John J.; Jamshidi, Mo

doi:10.1109/msmc.2020.2969031

Cited by 14 publications

(10 citation statements)

References 24 publications

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“…The HMD device that conducted the experiment was the HTC Vive pro, Oculus rift [27]. The controller used a Vive controller [22], Vive tracker [28], Oculus controller, Microsoft Xbox One Controller (the standard gamepad), and a morphable haptic controller [29] that provided a non-standard SDK. Haptic controllers were adjustable in length and thickness, and weight-centered movement was possible, making them suitable for content that utilizes various equipment.…”

Section: Resultsmentioning

confidence: 99%

A Flexible Input Mapping System for Next-Generation Virtual Reality Controllers

Lee

Shin

2021

Electronics

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This paper proposes an input mapping system that can transform various input signals from next-generation virtual reality devices to suit existing virtual reality content. Existing interactions of virtual reality content are developed based on input values for standardized commercial haptic controllers. This prevents the challenge of new ideas in content. However, controllers that are not compatible with existing virtual reality content have to take significant risks until commercialization. The proposed system allows content developers to map streams of new input devices to standard input events for use in existing content. This allows the reuse of code from existing content, even with new devices, effectively reducing development tasks. Further, it is possible to define a new input method from the perspective of content instead of the sensing results of the input device, allowing for content-specific standardization in content-oriented industries such as games and virtual reality.

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Section: Resultsmentioning

confidence: 99%

A Flexible Input Mapping System for Next-Generation Virtual Reality Controllers

Lee

Shin

2021

Electronics

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“…The measured errors of both VIVE sensors were below 0.4 • and 3 mm. In Flueratoru et al (2020) the HTC Vive tracker was adopted as ground truth system for UWB indoor localization, while in Lwowski et al (2020) the HTC Vive Tracker was employed for robot localization. An investigation of the HTC Vive tracking system for gait analysis was carried out by Guaitolini et al (2021) indicating that the device can accurately monitor gait parameters.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of the Oculus Rift S tracking system in room scale virtual reality

Monica

Aleotti

2022

Virtual Reality

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In specific virtual reality applications that require high accuracy it may be advisable to replace the built-in tracking system of the HMD with a third party solution. The purpose of this research work is to evaluate the accuracy of the built-in tracking system of the Oculus Rift S Head Mounted Display (HMD) in room scale environments against a motion capture system. In particular, an experimental evaluation of the Oculus Rift S inside-out tracking technology was carried out, compared to the performance of an outside-in tracking method based on the OptiTrack motion capture system. In order to track the pose of the HMD using the motion capture system the Oculus Rift S was instrumented with passive retro-reflective markers and calibrated. Experiments have been performed on a dataset of multiple paths including simple motions as well as more complex paths. Each recorded path contained simultaneous changes in both position and orientation of the HMD. Our results indicate that in room-scale environments the average translation error for the Oculus Rift S tracking system is about $$1.83$$ 1.83 cm, and the average rotation error is about $$0.77^\circ$$ 0 . 77 ∘ , which is 2 orders of magnitude higher than the performance that can be achieved using a motion capture system.

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“…The tracking is possible thanks to two infrared signals emitters called base stations (Figure 6-Top-right) and special active sensors that cover the surface of the headset, and controllers that intercept the infrared pulses can autonomously track their own position and orientation in the workspace determined by the field of view of the stations. The HTC Vive capabilities can be extended by means of small devices called Vive trackers (Figure 6-Bottom) [35] that implement Lighthouse technology too. They allow for a high degree of flexibility, making it possible to track items or body parts if correctly configured [36].…”

Section: Evaluation System Setupmentioning

confidence: 99%

Evaluation of Vision-Based Hand Tool Tracking Methods for Quality Assessment and Training in Human-Centered Industry 4.0

et al. 2022

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Smart industrial workstations for the training and evaluation of workers are an innovative approach to face the problems of manufacturing quality assessment and fast training. However, such products do not implement algorithms that are able to accurately track the pose of a hand tool that might also be partially occluded by the operator’s hands. In the best case, the already proposed systems roughly track the position of the operator’s hand center assuming that a certain task has been performed if the hand center position is close enough to a specified area. The problem of the pose estimation of 3D objects, including the hand tool, is an open and debated problem. The methods that lead to high accuracies are time consuming and require a 3D model of the object to detect, which is why they cannot be adopted for a real-time training system. The rise in deep learning has stimulated the search for better-performing vision-based solutions. Nevertheless, the problem of hand tool pose estimation for assembly and training procedures appears to not have been extensively investigated. In this study, four different vision-based methods based, respectively, on ArUco markers, OpenPose, Azure Kinect Body Tracking and the YOLO network have been proposed in order to estimate the position of a specific point of interest of the tool that has to be tracked in real-time during an assembly or maintenance procedure. The proposed approaches have been tested on a real scenario with four users handling a power drill simulating three different conditions during an assembly procedure. The performance of the methods has been evaluated and compared with the HTC Vive tracking system as a benchmark. Then, the advantages and drawbacks in terms of the accuracy and invasiveness of the method have been discussed. The authors can state that OpenPose is the most robust proposal arising from the study. The authors will investigate the OpenPose performance in more depth in further studies. The framework appears to be very interesting regarding its integration into a smart workstation for quality assessment and training.

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HTC Vive Tracker: Accuracy for Indoor Localization

Cited by 14 publications

References 24 publications

A Flexible Input Mapping System for Next-Generation Virtual Reality Controllers

A Flexible Input Mapping System for Next-Generation Virtual Reality Controllers

Evaluation of the Oculus Rift S tracking system in room scale virtual reality

Evaluation of Vision-Based Hand Tool Tracking Methods for Quality Assessment and Training in Human-Centered Industry 4.0

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