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This paper presents the theoretical foundation, practical implementation, and empirical evaluation of a glove for interaction with 3-D virtual environments. At the dawn of the “Spatial Computing Era”, where users continuously interact with 3-D Virtual and Augmented Reality environments, the need for a practical and intuitive interaction system that can efficiently engage 3-D elements is becoming pressing. Over the last few decades, there have been attempts to provide such an interaction mechanism using a glove. However, glove systems are currently not in widespread use due to their high cost and, we propose, due to their inability to sustain high levels of performance under certain situations. Performance deterioration has been observed due to the distortion of the local magnetic field caused by ordinary ferromagnetic objects present near the glove’s operating space. There are several areas where reliable hand-tracking gloves could provide a next generation of improved solutions, such as American Sign Language training and automatic translation to text and training and evaluation for activities that require high motor skills in the hands (e.g., playing some musical instruments, training of surgeons, etc.). While the use of a hand-tracking glove toward these goals seems intuitive, some of the currently available glove systems may not meet the accuracy and reliability levels required for those use cases. This paper describes our concept of an interaction glove instrumented with miniature magnetic, angular rate, and gravity (MARG) sensors and aided by a single camera. The camera used is an off-the-shelf red, green, and blue–depth (RGB-D) camera. We describe a proof-of-concept implementation of the system using our custom “GMVDK” orientation estimation algorithm. This paper also describes the glove’s empirical evaluation with human-subject performance tests. The results show that the prototype glove, using the GMVDK algorithm, is able to operate without performance losses, even in magnetically distorted environments.
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Detection and Tracking of Underwater Pipes using a Magnetic Camera
We present a magnetic camera system developed to detect ferrous or ferromagnetic objects. The main motivation is detection and tracking of underwater pipelines. Many industries, such as oil and gas, must perform inspection and maintenance of pipelines and automation is desirable. An electromagnet generates a static magnetic field which is read by an array of Hall-effect sensors. The presence of ferromagnetic materials distorts this field, which can be detected by the sensors and creates a magnetic image. The grid configuration of the camera allows for quick computation of the center of mass and general orientation of detected pipes, facilitating tracking. This camera is carried by an ROV and tested in a pool environment.
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- PAR ID:
- 10552106
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-5851-3
- Page Range / eLocation ID:
- 755 to 760
- Format(s):
- Medium: X
- Location:
- Bari, Italy
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/CASE59546.2024.10711684
