Augmented reality (AR) applications have gained much research and industry attention. Moreover, the mobile counterpart—mobile augmented reality (MAR) is one of the most explosive growth areas for AR applications in the mobile environment (e.g., smartphones). The technical improvements in the hardware of smartphones, tablets, and smart-glasses provide an advantage for the wide use of mobile AR in the real world and experience these AR applications anywhere. However, the mobile nature of MAR applications can limit users’ interaction capabilities, such as input and haptic feedback. In this survey, we analyze current research issues in the area of human-computer interaction for haptic technologies in MAR scenarios. The survey first presents human sensing capabilities and their applicability in AR applications. We classify haptic devices into two groups according to the triggered sense:
: touch, active surfaces, and mid-air;
: manipulandum, grasp, and exoskeleton. Due to MAR applications’ mobile capabilities, we mainly focus our study on wearable haptic devices for each category and their AR possibilities. To conclude, we discuss the future paths that haptic feedback should follow for MAR applications and their challenges.
Mobile Augmented Reality (AR), which overlays digital content on the real-world scenes surrounding a user, is bringing immersive interactive experiences where the real and virtual worlds are tightly coupled. To enable seamless and precise AR experiences, an image recognition system that can accurately recognize the object in the camera view with low system latency is required. However, due to the pervasiveness and severity of image distortions, an effective and robust image recognition solution for “in the wild” mobile AR is still elusive. In this article, we present CollabAR, an edge-assisted system that provides
distortion-tolerant image recognition
for mobile AR with
imperceptible system latency
. CollabAR incorporates both
image recognition modules in its design. The former enables distortion-adaptive image recognition to improve the robustness against image distortions, while the latter exploits the spatial-temporal correlation among mobile AR users to improve recognition accuracy. Moreover, as it is difficult to collect a large-scale image distortion dataset, we propose a Cycle-Consistent Generative Adversarial Network-based data augmentation method to synthesize realistic image distortion. Our evaluation demonstrates that CollabAR achieves over 85% recognition accuracy for “in the wild” images with severe distortions, while reducing the end-to-end system latency to as low as 18.2 ms.
The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research.
There is a discussion on the potential of augmented reality (AR), mobile technologies to enhance learning. This article presents: 1) the EduPARK project's first cycle of design-based research for the development of a mobile AR game-like app that aims to promote learning in an urban park, and 2) an experience of students using it in loco. The focus is the students' perceptions regarding the usability and functionality of the app. Data collection involved focus groups, questionnaires and app usage information. Data was submitted to content analysis and descriptive statistics. Results revealed an excellent usability of the EduPARK app, with an average system usability scale of 85.6. Overall, students reported that the app was enjoyable, easy to use and promoted learning; however, improvements and more evaluation experiences are needed to better understand mobile AR game-like learning in urban parks.
Augmented reality (AR) underpins many emerging mobile applications, but it increasingly requires more computation power for better machine understanding and user experience. While computation offloading promises a solution for high-quality and interactive mobile AR, existing methods work best for high-definition videos but cannot meet the real-time requirement for emerging 4K videos due to the long uploading latency. We introduce ACTOR, a novel computation-offloading framework for 4K mobile AR. To reduce the uploading latency, ACTOR dynamically and judiciously downscales the mobile video feed to be sent to the remote server. On the server-side, it leverages image super-resolution technology to scale back the received video so that high-quality object detection, tracking and rendering can be performed on the full 4K resolution. ACTOR employs machine learning to predict which of the downscaling resolutions and super-resolution configurations should be used, by taking into account the video content, server processing delay, and user expected latency. We evaluate ACTOR by applying it to over 2,000 4K video clips across two typical WiFi network settings. Extensive experimental results show that ACTOR consistently and significantly outperforms competitive methods for simultaneously meeting the latency and user-perceived video quality requirements.
Abstract. Modern technology is becoming a necessity of many destinations to stay competitive and attractive to the tourist. A new form of technology that is being used increasingly is Virtual and Augmented Reality (AR). The aim of this paper is to display the development of a mobile AR tourism application in urban heritage called PazinAR. Although Augmented Reality has passed the initial hype stage, the technology is just on the verge of being implemented in the tourism industry. This paper describes preparation, design, implementation and execution of prototype touristic application based on Augmented Reality (AR) technology. The application was made using Unity software and AR SDK Vuforia and exported as Android applications. Created application enables overlapping old photos with current view. Furthermore, several significant implications for AR Tourism research and practice are revealed.
Tourist experiences are shaped by the complexities of the individual visitor’s psychological factors, and it is widely known that tourists anticipate a positive experience from every trip made. Yet, the fact remains that travel is inextricably linked to the issues of geography and awareness and a misinterpretation of the attributes of a destination may lead to unlikely expectations that affect the entire experience. With the dynamic and interactive visualisation features offered by augmented reality (AR) on mobile phones and other smart handheld devices, this technology is viewed as being capable of closing the gap between tourist expectations and reality, thereby improving how tourists engage with their surroundings. Despite the known potential of this relatively new technology, its actual acceptance among the users is still minimal, especially in the Malaysian context. Considering this limitation, this study examined the extent of AR utilisation and its ability to influence the development of a tourists’ travel experience. The ‘Iskandar.my’ mobile AR app was used in this research to evaluate the tourists’ expectations, perception and satisfaction with the utilisation of this software platform to add value to their travel experience. The findings indicated that there was a statistically significant differences in the respondents’ experiences before and after using the AR content on the mobile app. The thrill associated with the use of this advanced technology was the primary factor in their satisfaction with the AR function. However, the lack of variety in the attractions covered, as well as the app’s currently limited offerings, were noted as factors that could affect the ‘Iskandar. my’ apps competitiveness with regard to other travel-related apps. Therefore, this researcher recommends that the developer of the app improve the design and service dimensions of the app to meet users’ travel needs.
<p class="0abstract">Augmented reality (AR) is an emerging technology that has permeated different spheres of life, one of them is education, and specifically the teaching-learning process at different educational levels and objects of study. For this reason, this paper presents the development of a learning model of quadric surfaces mediated by a mobile AR application and based on didactic engineering. The model was applied to a group of environmental engineering students of the Catholic University of Manizales. To obtain information on the use of the application and the learning results obtained, some intervention instruments were developed. The students stated that the use of AR allowed them to better understand the concepts of quadric surfaces, even more so in a time of pandemic by COVID-19, where education was highly measured by ICTs.</p>
Marine knowledge is such an important part of education that it has been integrated into various subjects and courses across educational levels. Previous research has indicated the importance of AR assisted students’ learning during the learning process. This study proposed the AR Oyster Learning System (AROLS) that integrates mobile AR with a marine education teaching strategy for teachers in primary schools. To evaluate the effectiveness of the proposed approach, an experiment was conducted in a primary school natural science course regarding oysters. The participants consisted of 22 fourth-grade students. The experimental group comprised 11 students who learned with the AROLS learning approach and the control group comprised 11 students who learned with the conventional multimedia learning approach. The results indicate that (1) students were interested in the AR learning approach, (2) students’ learning achievement and motivation were improved by the AR learning approach, (3) students acquired the target knowledge through the oyster course, and (4) students learned the importance of sustainability when taking online courses at home during the pandemic.