Self-calibrated multi-sensor wearable for hand tracking and modeling

Abstract: We present a multi-sensor system for consistent 3D hand pose tracking and modeling that leverages the advantages of both wearable and optical sensors. Specifically, we employ a stretch-sensing soft glove and three IMUs in combination with an RGB-D camera. Different sensor modalities are fused based on the availability and confidence estimation, enabling seamless hand tracking in challenging environments with partial or even complete occlusion. To maximize the accuracy while maintaining high ease-of-use, we propose an automated user calibration that uses the RGB-D camera data to refine both the glove mapping model and the multi-IMU system parameters. Extensive experiments show that our setup outperforms the wearable-only approaches when the hand is in the field-of-view and outplays the camera-only methods when the hand is occluded

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
IEEE transactions on visualization and computer graphics. - 29, 3 (2023) , 1769-1784, ISSN: 1941-0506

Event
Veröffentlichung
(where)
Freiburg
(who)
Universität
(when)
2024
Creator
Gosala, Nikhil
Wang, Fangjinhua
Cui, Zhaopeng
Liang, Hanxue
Glauser, Oliver
Wu, Shihao
Sorkine-Hornung, Olga

DOI
10.1109/tvcg.2021.3131230
URN
urn:nbn:de:bsz:25-freidok-2537782
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
25.03.2025, 1:48 PM CET

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Associated

  • Gosala, Nikhil
  • Wang, Fangjinhua
  • Cui, Zhaopeng
  • Liang, Hanxue
  • Glauser, Oliver
  • Wu, Shihao
  • Sorkine-Hornung, Olga
  • Universität

Time of origin

  • 2024

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