Abstract
Numerous applications of Virtual Reality (VR) and Augmented Reality (AR) continue to emerge. However, many of the current mechanisms to provide input in those environments still require the user to perform actions (e.g., press a number of buttons, tilt a stick) that are not natural or intuitive. It would be desirable to enable users of 3D virtual environments to use natural hand gestures to interact with the environments. The implementation of a glove capable of tracking the movement and configuration of a user’s hand has been pursued by multiple groups in the past. One of the most recent approaches consists of tracking the motion of the hand and fingers using miniature sensor modules with magnetic and inertial sensors. Unfortunately, the limited quality of the signals from those sensors and the frequent deviation from the assumptions made in the design of their operations have prevented the implementation of a tracking glove able to achieve high performance and large-scale acceptance. This paper describes our development of a proof-of-concept glove that incorporates motion sensors and a signal processing algorithm designed to maintain high tracking performance even in locations that are challenging to these sensors, (e.g., where the geomagnetic field is distorted by nearby ferromagnetic objects). We describe the integration of the required components, the rationale and outline of the tracking algorithms and the virtual reality environment in which the tracking results drive the movements of the model of a hand. We also describe the protocol that will be used to evaluate the performance of the glove.
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References
Advanced Navigation: Inertial Measurement Unit (IMU) – An Introduction. Tech Articles 8 January 2024. https://www.advancednavigation.com/tech-articles/inertial-measurement-unit-imu-an-introduction/. 10 Jan 2024
Aggarwal, P., Syed, Z., Noureldin, A., El-Sheimy, N.: MEMS-Based Integrated Navigation. Artech House GNSS Technology and Applications Series, vol. xiii, 197 p. Artech House, Boston, Mass.; London (2010)
Chen, Y., Wang, Q., Chen, H., Song, X., Tang, H., Tian, M.: An overview of augmented reality technology. J. Phys. Conf. Ser. 1237(2), 022082 (2019)
de Vries, W.H.K., Veeger, H.E.J., Baten, C.T.M., van der Helm, F.C.T.: Magnetic distortion in motion labs, implications for validating inertial magnetic sensors. Gait Posture 29(4), 535–541 (2009)
Dipietro, L., Sabatini, A.M., Dario, P.: A survey of glove-based systems and their applications. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 38(4), 461–482 (2008)
Foxlin, E.: Motion tracking requirements and technologies. In: Stanney, K.M. (ed.) Handbook of Virtual Environments, Design, Implementation, and Applications. Lawrence Earlbaum Associates (2002)
Hanson, A.: Visualizing quaternions. Morgan Kaufmann Series in Interactive 3D Technology, vol. xxxi, 498 p. Morgan Kaufmann, San Francisco, Amsterdam, Boston. Elsevier Science distributor (2006)
Intel: Intel® RealSenseTM Product Family D400 Series Datasheet 2023 p. https://www.intelrealsense.com/download/21345/?tmstv=1697035582
Ip, H.H.S., Chan, C.S.: Dynamic simulation of human hand motion using an anatomically correct hierarchical approach. In: 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, vol. 1302, pp. 1307–1312. IEEE (1997)
Kalman, R.E.: A new approach to linear filtering and prediction problems. J. Basic Eng. 82(1), 35–45 (1960)
Kortier, H.G., Sluiter, V.I., Roetenberg, D., Veltink, P.H.: Assessment of hand kinematics using inertial and magnetic sensors. J. Neuroeng. Rehabil. 11, 70 (2014)
Kuipers, J.B.: Quaternions and rotation sequences: a primer with applications to orbits, aerospace, and virtual reality, vol. xxii, 371 p. Princeton University Press, Princeton, N.J. (1999)
López-Belmonte, J., Moreno-Guerrero, A.-J., López-Núñez, J.-A., Hinojo-Lucena, F.-J.: Augmented reality in education. A scientific mapping in web of science. Interact. Learn. Environ. 31(4), 1860–1874 (2023)
Madgwick, S.: An efficient orientation filter for inertial and inertial/magnetic sensor arrays. Report x-io Univ. Bristol (UK) 25, 113–118 (2010)
Mahony, R., Hamel, T., Pflimlin, J.M.: Complementary filter design on the special orthogonal group SO (3). In: 44th IEEE Conference on Decision and Control, pp. 1477–1484. IEEE (2005)
Manuri, F., Sanna, A.: A survey on applications of augmented reality. ACSIJ Adv. Comput. Sci. Int. J. 5(1), 18–27 (2016)
Nuitrack: NUITRACK SDK, 10 January 2024. https://nuitrack.com/#api
Ratchatanantakit, N., O-larnnithipong, N., Barreto, A., Tangnimitchok, S.: Consistency study of 3D magnetic vectors in an office environment for IMU-based hand tracking input development. In: Kurosu, M. (ed.) Human-Computer Interaction. Recognition and Interaction Technologies. LNCS, vol. 11567, pp. 377–387. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22643-5_29
Sonchan, P., Ratchatanantakit, N., O-larnnithipong, N., Adjouadi, M., Barreto, A.: A self-contained approach to MEMS MARG orientation estimation for hand gesture tracking in magnetically distorted environments. In: Kurosu, M., Hashizume, A. (eds.) HCII 2023. LNCS, vol. 14011, pp. 585–602. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-35596-7_38
Vince, J.: Quaternions for Computer Graphics, p. xiv, 140 p. Springer, London; New York (2011). https://doi.org/10.1007/978-0-85729-760-0
Woodman, O.J.: An introduction to inertial navigation. University of Cambridge (2007)
Xiaoping, Y., Aparicio, C., Bachmann, E.R., McGhee, R.B.: Implementation and experimental results of a quaternion-based Kalman filter for human body motion tracking. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation (2005)
YostLabs: 3-Space Nano IC - Product Description Page. Product Description for the 3-Space Nano IC MARG. https://yostlabs.com/product/3-space-nano/. Cited 5 Feb 2023
Acknowledgements
This work was supported by the US National Science Foundation grant CNS-1920182. Mr. Pontakorn Sonchan was supported by FIU’s DYF fellowship.
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Sonchan, P., Ratchatanantakit, N., O-larnnithipong, N., Adjouadi, M., Barreto, A. (2024). Proof-of-Concept MARG-Based Glove for Intuitive 3D Human-Computer Interaction. In: Chen, J.Y.C., Fragomeni, G. (eds) Virtual, Augmented and Mixed Reality. HCII 2024. Lecture Notes in Computer Science, vol 14707. Springer, Cham. https://doi.org/10.1007/978-3-031-61044-8_20
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