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Conference Papers Year : 2024

TriPad: Touch Input in AR on Ordinary Surfaces with Hand Tracking Only

Caroline Appert
Stéphanie Rey
Houssem Saidi
  • Function : Author
  • PersonId : 1362029
Emmanuel Pietriga

Abstract

TriPad enables opportunistic touch interaction in Augmented Reality using hand tracking only. Users declare the surface they want to appropriate with a simple hand tap gesture. They can then use this surface at will for direct and indirect touch input. TriPad only involves analyzing hand movements and postures, without the need for additional instrumentation, scene understanding or machine learning. TriPad thus works on a variety of flat surfaces, including glass. It also ensures low computational overhead on devices that typically have a limited power budget. We describe the approach, and report on two user studies. The first study demonstrates the robustness of TriPad's hand movement interpreter on different surface materials. The second study compares TriPad against direct mid-air AR input techniques on both discrete and continuous tasks and with different surface orientations. TriPad achieves a better speed-accuracy trade-off overall, improves comfort and minimizes fatigue.
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hal-04497640 , version 1 (10-03-2024)

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Camille Dupré, Caroline Appert, Stéphanie Rey, Houssem Saidi, Emmanuel Pietriga. TriPad: Touch Input in AR on Ordinary Surfaces with Hand Tracking Only. CHI 2024 - The 42nd SIGCHI conference on Human Factors in computing systems, ACM, May 2024, Honolulu, HI, USA, United States. ⟨10.1145/3613904.3642323⟩. ⟨hal-04497640⟩
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