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Article Dans Une Revue Multimodal Technologies and Interaction Année : 2021

User Behavior Adaptive AR Guidance for Wayfinding and Tasks Completion

Alexis Paljic
Alexis Roux
  • Fonction : Auteur
Martin Herbeth
  • Fonction : Auteur


Augmented reality (AR) is widely used to guide users when performing complex tasks, for example, in education or industry. Sometimes, these tasks are a succession of subtasks, possibly distant from each other. This can happen, for instance, in inspection operations, where AR devices can give instructions about subtasks to perform in several rooms. In this case, AR guidance is both needed to indicate where to head to perform the subtasks and to instruct the user about how to perform these subtasks. In this paper, we propose an approach based on user activity detection. An AR device displays the guidance for wayfinding when current user activity suggests it is needed. We designed the first prototype on a head-mounted display using a neural network for user activity detection and compared it with two other guidance temporality strategies, in terms of efficiency and user preferences. Our results show that the most efficient guidance temporality depends on user familiarity with the AR display. While our proposed guidance has not proven to be more efficient than the other two, our experiment hints toward several improvements of our prototype, which is a first step in the direction of efficient guidance for both wayfinding and complex task completion.

Dates et versions

hal-03399130 , version 1 (23-10-2021)



Alexis Paljic, Camille Truong-Allié, Alexis Roux, Martin Herbeth. User Behavior Adaptive AR Guidance for Wayfinding and Tasks Completion. Multimodal Technologies and Interaction, 2021, 5 (11), pp.65. ⟨10.3390/mti5110065⟩. ⟨hal-03399130⟩
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