User Interactions for Augmented Reality Smart Glasses: A Comparative Evaluation of Visual Contexts and Interaction Gestures

Kim, Minseok; Choi, Sung Ho; Park, Kyeong-Beom; Lee, Jae Yeol

doi:10.3390/app9153171

Cited by 31 publications

(22 citation statements)

References 44 publications

(58 reference statements)

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“…Some research has proposed details of the content structure for resource management as another issue to provide AR datasets. Kim et al presented an AR content structure for building mobile AR applications in HTML5, as on the Web [28]. They used an extended presentation logic of HTML to apply current web architecture and a referencing method with matching between physical and virtual resources.…”

Section: Data Management For Physical Objectsmentioning

confidence: 99%

“…Regarding the IoT, AR-based interaction and object control have been shown to be much more intuitive, direct, and helpful compared to graphical user interface (GUI) - and menu-based interfaces on handheld devices, for example. GUI- and menu-based interfaces still have the advantage of consistent design and guaranteed minimum usability [28]. Thus, our proposal is to develop a framework for AR interaction considering the object characteristics and the impact of various kinds of AR devices.…”

Section: Future Research Directionsmentioning

confidence: 99%

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AR Enabled IoT for a Smart and Interactive Environment: A Survey and Future Directions

Kim

2019

Sensors

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Accompanying the advent of wireless networking and the Internet of Things (IoT), traditional augmented reality (AR) systems to visualize virtual 3D models of the real world are evolving into smart and interactive AR related to the context of things for physical objects. We propose the integration of AR and IoT in a complementary way, making AR scalable to cover objects everywhere with an acceptable level of performance and interacting with IoT in a more intuitive manner. We identify three key components for realizing such a synergistic integration: (1) distributed and object-centric data management (including for AR services); (2) IoT object-guided tracking; (3) seamless interaction and content interoperability. We survey the current state of these respective areas and herein discuss research on issues about realizing a future smart and interactive living environment.

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Section: Data Management For Physical Objectsmentioning

confidence: 99%

Section: Future Research Directionsmentioning

confidence: 99%

AR Enabled IoT for a Smart and Interactive Environment: A Survey and Future Directions

Kim

2019

Sensors

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“…Augmented reality is considered to provide user-centric information more easily in various environments by embedding visual information onto the real objects directly. In particular, the AR-based visualization of manufacturing information, called industrial AR, can provide more effective task assistance, which can reduce a worker’s cognitive load and increase work efficiency [ 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach to Industrial Augmented Reality Using Deep Learning-Based Facility Segmentation and Depth Prediction

Kim

Choi

Park

et al. 2021

Sensors

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Typical AR methods have generic problems such as visual mismatching, incorrect occlusions, and limited augmentation due to the inability to estimate depth from AR images and attaching the AR markers onto physical objects, which prevents the industrial worker from conducting manufacturing tasks effectively. This paper proposes a hybrid approach to industrial AR for complementing existing AR methods using deep learning-based facility segmentation and depth prediction without AR markers and a depth camera. First, the outlines of physical objects are extracted by applying a deep learning-based instance segmentation method to the RGB image acquired from the AR camera. Simultaneously, a depth prediction method is applied to the AR image to estimate the depth map as a 3D point cloud for the detected object. Based on the segmented 3D point cloud data, 3D spatial relationships among the physical objects are calculated, which can assist in solving the visual mismatch and occlusion problems properly. In addition, it can deal with a dynamically operating or a moving facility, such as a robot—the conventional AR cannot do so. For these reasons, the proposed approach can be utilized as a hybrid or complementing function to existing AR methods, since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions. Quantitative and qualitative analyses verify the advantage of the proposed approach compared with existing AR methods. Some case studies also prove that the proposed method can be applied not only to manufacturing but also to other fields. These studies confirm the scalability, effectiveness, and originality of this proposed approach.

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“…Nevertheless, there are usability problems related to human-machine interactions that can limit the spread of SG devices for AR technology [10,22]. These are linked to low computational power and that the available applications are still basic [5], thus the final user may have problems with using the SG if proper applications related to his field of work are not available.…”

Section: Introductionmentioning

confidence: 99%

Performance and Usability of Smartglasses for Augmented Reality in Precision Livestock Farming Operations

et al. 2020

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In recent years, smartglasses for augmented reality are becoming increasingly popular in professional contexts. However, no commercial solutions are available for the agricultural field, despite the potential of this technology to help farmers. Many head-wearable devices in development possess a variety of features that may affect the smartglasses wearing experience. Over the last decades, dairy farms have adopted new technologies to improve their productivity and profit. However, there remains a gap in the literature as regards the application of augmented reality in livestock farms. Head-wearable devices may offer invaluable benefits to farmers, allowing real-time information monitoring of each animal during on-farm activities. The aim of this study was to expand the knowledge base on how augmented reality devices (smartglasses) interact with farming environments, focusing primarily on human perception and usability. Research has been conducted examining the GlassUp F4 smartglasses during animal selection process. Sixteen participants performed the identification and grouping trials in the milking parlor, reading different types of contents on the augmented reality device optical display. Two questionnaires were used to evaluate the perceived workload and usability of the device. Results showed that the information type could influence the perceived workload and the animal identification process. Smart glasses for augmented reality were a useful tool in the animal genetic improvement program offering promising opportunities for adoption in livestock operations in terms of assessing data consultation and information about animals.

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User Interactions for Augmented Reality Smart Glasses: A Comparative Evaluation of Visual Contexts and Interaction Gestures

Cited by 31 publications

References 44 publications

AR Enabled IoT for a Smart and Interactive Environment: A Survey and Future Directions

AR Enabled IoT for a Smart and Interactive Environment: A Survey and Future Directions

A Hybrid Approach to Industrial Augmented Reality Using Deep Learning-Based Facility Segmentation and Depth Prediction

Performance and Usability of Smartglasses for Augmented Reality in Precision Livestock Farming Operations

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