Supporting interaction in augmented reality assisted industrial processes using a CNN-based semantic layer

Izquierdo-Domenech, Juan; Linares-Pellicer, Jordi; Orta-Lopez, Jorge

doi:10.1109/aivr50618.2020.00014

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…While well received and preferred over the PC, they did not explore behaviors related to the geometric properties of the objects. In the same context, the work by Izquierdo-Domenech et al [4] and Chidambaram et al [22] used computer vision to classify objects from the environment. Izquierdo-Domenech et al [4] present a more automatic approach to adding semantic information to objects in the scene.…”

Section: Augmented Reality Authoring Toolsmentioning

confidence: 99%

“…In the same context, the work by Izquierdo-Domenech et al [4] and Chidambaram et al [22] used computer vision to classify objects from the environment. Izquierdo-Domenech et al [4] present a more automatic approach to adding semantic information to objects in the scene. In this paper, we focus on the evaluation of a human-inthe-loop approach where geometrical constraints are defined by the subject matter expert using an authoring tool, as seen in AffordIt!…”

Section: Augmented Reality Authoring Toolsmentioning

confidence: 99%

“…In a given scenario, virtual objects possess attributes and behaviors that can infer some kind of instruction in the scene, such as in [2,3] in the form of audio and visual cues. Conversely, some objects demand more complex actions, such as rotating a knob or pressing a button, as in [4]; opening doors or compartments, as in the examples in [5]; or even deforming the geometries of objects, like the spring scenario from [6].…”

Section: Introductionmentioning

confidence: 99%

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Authoring Moving Parts of Objects in AR, VR and the Desktop

Vargas González,

Williamson,

LaViola

2023

MTI

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Creating digital twins of real objects is becoming more popular, with smartphones providing 3D scanning capabilities. Adding semantics to the reconstructed virtual objects is important to possibly reproduce training scenarios that otherwise could demand significant resources or happen in dangerous scenarios in some cases. The aim of this work is to evaluate the usability of authoring object component behaviors in immersive and non-immersive approaches. Therefore, we present an evaluation of the perceived ease of use to author moving parts of objects under three different conditions: desktop, augmented reality (AR) and virtual reality (VR). This paper provides insights into the perceived benefits and issues that domain experts might encounter when authoring geometrical component behaviors across each interface. A within-subject study is the major contribution of this work, from which is presented an analysis based on the usability, workload and user interface preferences of participants in the study. To reduce confounding variables in the study, we ensured that the virtual objects and the environment used for the evaluation were digital twins of the real objects and the environment that the experiment took place in. Results show that the desktop interface was perceived as more efficient and easier to use based on usability and workload measures. The desktop was preferred for performing component selection but no difference was found in the preference for defining a behavior and visualizing it. Based on these results, a set of recommendations and future directions are provided to achieve a more usable, immersive authoring experience.

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Section: Augmented Reality Authoring Toolsmentioning

confidence: 99%

Section: Augmented Reality Authoring Toolsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Authoring Moving Parts of Objects in AR, VR and the Desktop

Vargas González,

Williamson,

LaViola

2023

MTI

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An Edge Cloud Based Coordination Platform for Multi-user AR Applications

Sonkoly,

Nagy,

Dóka

et al. 2024

J Netw Syst Manage

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Augmented Reality (AR) applications can reshape our society enabling novel ways of interactions and immersive experiences in many fields. However, multi-user and collaborative AR applications pose several challenges. The expected user experience requires accurate position and orientation information for each device and precise synchronization of the respective coordinate systems in real-time. Unlike mobile phones or AR glasses running on battery with constrained resource capacity, cloud and edge platforms can provide the computing power for the core functions under the hood. In this paper, we propose a novel edge cloud based platform for multi-user AR applications realizing an essential coordination service among the users. The latency critical, computation intensive Simultaneous Localization And Mapping (SLAM) function is offloaded from the device to the edge cloud infrastructure. Our solution is built on open-source SLAM libraries and the Robot Operating System (ROS). Our contribution is threefold. First, we propose an extensible, edge cloud based AR architecture. Second, we develop a proof-of-concept prototype supporting multiple devices and building on an AI-based SLAM selection component. Third, a dedicated measurement methodology is described, including energy consumption aspects as well, and the overall performance of the system is evaluated via real experiments.

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