Mobile Augmented Reality System Research Articles

Realization of Mobile Augmented Reality System Based on Image Recognition

With the development of computation technology, the augmented reality (AR) is widely applied in many fields as well as the image recognition. However, the AR application on mobile platform is not developed enough in the past decades due to the capability of the mobile processors. In recent years, the performance of mobile processors has changed rapidly, which makes it comparable to the desktop processors. This paper proposed and realized an AR system to be used on the Android mobile platform based on the image recognition through EasyAR engine and Unity 3D development tools. In this system, the image recognition could be done locally and/or using cloud recognition. Test results show that the cloud-based recognition is more efficient and accuracy than the local recognition for the mobile AR when there are more images to be recognized at the same time.

A Survey on Mobile Augmented Reality With 5G Mobile Edge Computing: Architectures, Applications, and Technical Aspects

The Augmented Reality (AR) technology enhances the human perception of the world by combining the real environment with the virtual space. With the explosive growth of powerful, less expensive mobile devices, and the emergence of sophisticated communication infrastructure, Mobile Augmented Reality (MAR) applications are gaining increased popularity. MAR allows users to run AR applications on mobile devices with greater mobility and at a lower cost. The emerging 5G communication technologies act as critical enablers for future MAR applications to achieve ultra-low latency and extremely high data rates while Multi-access Edge Computing (MEC) brings enhanced computational power closer to the users to complement MAR. This paper extensively discusses the landscape of MAR through the past and its future prospects with respect to the 5G systems and complementary technology MEC. The paper especially provides an informative analysis of the network formation of current and future MAR systems in terms of cloud, edge, localized, and hybrid architectural options. The paper discusses key application areas for MAR and their future with the advent of 5G technologies. The paper also discusses the requirements and limitations of MAR technical aspects such as communication, mobility management, energy management, service offloading and migration, security, and privacy and analyzes the role of 5G technologies.

Mobile augmented reality technology for design and implementation of library document push system

Through mobile augmented reality interaction, the library can keep abreast of the user’s current information orientation and lay the foundation for the further establishment of a personal information database. At the same time, on the basis of network interaction, it plays a good guiding role for the construction of library document resources, ensuring the effective use of document resources. This paper analyzes the key technologies of the mobile augmented reality system, including virtual graphics rendering technology, camera tracking and positioning technology, display technology and so on. To solve the problem of human error caused by design deviation in the current mobile augmented reality library document push, a new data visualization and interactive design process is proposed. On the basis of analyzing user needs and comparing augmented reality library document push with traditional library document push, the demand is transformed into tasks. We use a combination of overview and detail to lay out the visual elements. The progressive interactive method is used to organize discrete data views and generate interactive interfaces. The system test results show that the library document pushing system designed in this paper can effectively reduce the memory consumption of the system, improve the refresh frame rate of the view and improve the user’s interactive fluency.

Real-time Object Recognition with Pose Initialization for Large-scale Standalone Mobile Augmented Reality

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

Joint Server Assignment and Resource Management for Edge-Based MAR System

Mobile Augmented Reality (MAR) applications usually contain computation-intensive tasks which far outstrip the capability of mobile devices. One way to overcome this is offloading computation-intensive MAR tasks to remote clouds. However, the wide area network delay is hard to reduce. Thanks to edge computing, we can offload MAR tasks to nearby servers. Prior studies focus on either single-task MAR applications offloading or dependent tasks offloading for a single user. In this article, we study the offloading decision of MAR applications from multiple users, each of which is comprised of a chain of dependent tasks, over a generic cloud-edge system consisting of a group of heterogeneous edge servers and remote clouds. We formulate the Multi-user Multi-task MAR Application Scheduling (M3AS) problem, which is NP-hard. We present Mutas, an efficient scheduling algorithm that jointly optimizes server assignment and resource management. We also consider the online version of M3AS and present OnMutas. Extensive evaluations demonstrate that both Mutas and OnMutas can significantly reduce the service delays of MAR applications when compared to three other heuristics.

Impact of Mobile Augmented Reality System on Cognitive Behavior and Performance during Rebar Inspection Tasks

AbstractMobile augmented reality (MAR) enhances the real world through the superimposition of computer-generated information while not interfering with a users’ mobility, having great potential to ...

LAR: a low-power, high-precision mobile phone-based AR system

Mobile crowd sensing is a novel large-scale sensing pattern, which applies users’ smart devices to analyze social context and human activity, and then learns the intelligent information serving for various innovative services. An augmented reality (AR) system can bring more authentic experience for human life, and more and more scholars are increasingly interested in this technology. However, there are some problems in the previous methods, such as the expensive deployment, low accuracy, and high latency. These problems greatly limit the application of augmented reality systems. In this paper, we design a lightweight augmented reality system, called LAR, which can recognize the target object quickly and precisely by using a feature matching algorithm. In LAR, the target object is shot twice to get the distance between the user and the object, and we take the distance as the feature of the target object. Furthermore, the feature extraction algorithm, named s-SURF, is designed to extract image features. LAR combines the distance with image feature and then matches with these images stored in database. In addition, the flutter-free algorithm is used to denoise and get a clearer image. Finally, we design a prototype system to evaluate LAR performance. The accuracy of LAR is 86%, and the time delay achieves 141 ms.

Augmented Reality Mobile Learning System: Study to Improve PSTs’ Understanding of Mathematical Development

Augmented Reality research in mobile learning systems so far have not especially to improve Preservice Students Teachers' (PSTs) geometry understanding in mathematical development. Studies conducted in this study basically use a case study. This research aims to develop a mobile augmented reality system for PSTs learning so that it can be used to improve PSTs understanding of mathematics development includes doing, image-making, an image having, property noticing, formalizing, observing, structuring and inventing. In this development, PSTs can understand the understanding of the geometry transformation is a translation, reflection, rotation, and dilatation.

The effect of paper-based manual and stereoscopic-based mobile augmented reality systems on knowledge retention

Augmented reality technology is attracting increased attention, given the popularity of the smartphone. The utilisation of the smartphone with AR technology is also enabling mobile augmented reality (MAR) to become accessible. Stereoscopic vision offers users the benefit of depth perception, which can help improve user memory. Therefore, this study aims to investigate the effect on knowledge retention using MAR with stereoscopic vision. An experiment to compare a stereoscopic-based MAR application and a paper-based manual was designed to test the participants’ knowledge retention on a product part and disassembly process. The developed MAR adopted a smartphone and headset case to provide a stereoscopic view to the user. The experiment consisted of both pre-test and post-test phases where the pre-test phase examined the participant’s knowledge about the product, and the post-test phase focused on how much information the participants could recall. The post-test phase was conducted after 48 h following the pre-test phase since long-term memory required several hours in which to stabilise. The results showed that the MAR group had an advantage over the paper-based manual group for both information retentions having a mean score of 8.89 from the MAR group, compared with 6.33 for the paper-based manual group. Moreover, the MAR group was observed to have fewer errors in the post-test with a mean score of 0.53, whereas the paper-based achieved a score of 2.2. This result indicated that the MAR group and the paper-based manual group had equivalent performance in the completion time without the assistance tool. In addition, MAR had a better mean score for the subjective feedback (usefulness = 4.47, ease of use 4.18 and satisfaction = 4.07).

Optimizing the Learning Performance in Mobile Augmented Reality Systems With CNN

It is an essential goal for future wireless networks to provide better artificial intelligent services. In this paper, we investigate the joint communication and computation resource optimization in the mobile edge learning system to support augmented reality applications, where the convolutional neural networks (CNNs) are deployed at the edge server. For such a system, we first develop a delay model to characterize the relation between the computation latency and the input image size of general CNN models. Then, we formulate a mixed integer nonlinear optimization problem to maximize the system computation capacity under the constraints of learning accuracy, end-to-end latency, and energy consumption. To solve this problem, we first investigate maximizing the system learning accuracy under the communication and computation resource constraints. The optimal resource allocation policy can be achieved by a low-complexity search algorithm. We further prove that the original problem is NP-hard and propose an efficient heuristic algorithm with a newly-developed offloading priority function. An upper bound for the proposed algorithm is also derived. Finally, test results validate the applicability of the delay model and demonstrate the performance improvement of the proposed algorithm as compared with the existing algorithms.

A Mobile Augmented Reality System for the Real-Time Visualization of Pipes in Point Cloud Data with a Depth Sensor

Augmented reality (AR) is a useful visualization technology that displays information by adding virtual images to the real world. In AR systems that require three-dimensional information, point cloud data is easy to use after real-time acquisition, however, it is difficult to measure and visualize real-time objects due to the large amount of data and a matching process. In this paper we explored a method of estimating pipes from point cloud data and visualizing them in real-time through augmented reality devices. In general, pipe estimation in a point cloud uses a Hough transform and is performed through a preprocessing process, such as noise filtering, normal estimation, or segmentation. However, there is a disadvantage in that the execution time is slow due to a large amount of computation. Therefore, for the real-time visualization in augmented reality devices, the fast cylinder matching method using random sample consensus (RANSAC) is required. In this paper, we proposed parallel processing, multiple frames, adjustable scale, and error correction for real-time visualization. The real-time visualization method through the augmented reality device obtained a depth image from the sensor and configured a uniform point cloud using a voxel grid algorithm. The constructed data was analyzed according to the fast cylinder matching method using RANSAC. The real-time visualization method through augmented reality devices is expected to be used to identify problems, such as the sagging of pipes, through real-time measurements at plant sites due to the spread of various AR devices.

Mobile Pervasive Augmented Reality Systems—MPARS

After briefly introducing aspects concerning Mobile Augmented Reality Systems, this article delves into the evolution of these systems as pervasive technology. The work debates also on acceptance of this technology in the context of outdoor applications. The need to develop context-aware, close-to-real-time feedback mechanisms that take into consideration a continuous measurement of Quality of Experience is also discussed. For this purpose, the work goes over how to integrate user preferences into context-aware feedback systems, proposing a theoretical model for measuring Quality of Experience. The model is derived from an analysis of previous technology adoption models and incorporates the knowledge of user preferences. This knowledge has been gathered via a public questionnaire.

An epistemological assessment of learning nutritional information with augmented reality

PurposeThis study aims to investigate whether epistemological assessment is a suitable approach to evaluate students’ learning of dietary knowledge via the use of an augmented reality (AR) information system. Students’ perceived dietary knowledge was compared before and after learning with the AR system. Two major questions were addressed: Did students improve their understanding of dietary knowledge after the use of AR information system? Did students gain more appropriate understanding of dietary knowledge after the use of AR information system?Design/methodology/approachA mixed-methods approach was used in the study. The mobile AR system was used among 65 volunteered non-nutrition-major college students recruited in campus. For promoting epistemological development of personal dietary knowledge, students practiced with life experiences to access daily dietary information. Pre- and post-tests of students’ understanding of dietary knowledge were compared. Interviews with 20 students were used for gathering in-depth research data to analyse students’ epistemological understanding of dietary knowledge.FindingsThe epistemological assessment indicated an improvement in learning after the use of the AR system. Students gradually gained awareness of dietary knowledge and changed their perceptions of their dietary behaviours. Epistemological approaches to the analysis of students’ conceptual change in dietary knowledge revealed a significant increase in the mean nutritional concepts (p < 0.01) and a decrease in their mean misconceptions (p < 0.001) after learning via the mobile nutrition monitoring system. Learning assessment of 65 students also indicated a significant increase from the post-test after learning with the system (p < 0.0001).Research limitations/implicationsThis study might have its limitations, as it only assessed learning using a pretest-posttest design for a specific learning context over a short period of learning time. The use of interviews based on the epistemological approach might have its limitations in the interpretations of the phenomenon. Future implementations can also be extended to different populations to promote self-monitoring dietary behaviours.Originality/valueThe findings of this study will contribute to the application of AR in learning about dietary knowledge. The research involving in-depth observation of students’ learning relevant to personal nutritional information needs via mobile AR might provide potential contributions to dietitian professionals and health education.

RETRACTED ARTICLE: The differences in pleasing value and learning performance among different groups using mobile augmented reality system for cultural environment learning

Mobile Augmented Reality (MAR) has becomes more widely used and provides the great context of an immersive virtual learning environment. However, sometimes the learning effect is influenced by the pleasing value, which is always subjective and learning driven. In order to ensure a successful launch of the MAR cultural interactive learning tool, it is extremely important to predict the pleasing value of design alternatives based on the common language understood by students. For learners, in the learning process, the value of pleasure comes from the improvement of external emotional interest as well as internal cognitive interest that learners already have. This research will examine if students have problems with operating the MAR, and to understand whether they have pleasing value and a learning performance. Thus, this research has proposed a difference of visual perception and a construction for the evaluation of pleasing value as well as the culture of learning performance between media students and students in other majors. The research team has chosen different cultural temples in Shi-lin and Tam-sui in Taiwan using the MAR systems to evaluate the correctness and speed of the reaction in between the two groups represented as: the experimental group and the control group. The research objects will be the second year/sophomore studentsat Taipei University of Marine Technology. There were two classes with different majors and there were 35 students in each class. This research took one of the classes as the experimental group with “MAR empirical teaching in cultural and environmental learning” and other class will be the control group using the traditional teaching method. The result from the experiment and the ANCOVA analysis indicates: (1) Based on the results of experiments, the participants appreciated the MAR approach. The learning performance of the students did improve significantly via ACNOVA. (2) The experimental group has a more significant effect compared to the control group in the aspect from the four learning performance constructions: stylistic, cultural value, cultural characterization and innovation services. (3) Through the bi-variance statistical analysis (One-Way, ANOVA), there was a significant positive correlation between pleasing value and the improvement of post-learning interest in the experimental group. This research found that based on the exploration factor from that the results the interfaces were built on a mobile phone with a touch-screen can be a model for the effectiveness examination, It can also expand the MAR application scope by incorporating it into teaching.

A Geometry-Based Point Cloud Reduction Method for Mobile Augmented Reality System

In this paper, a geometry-based point cloud reduction method is proposed, and a real-time mobile augmented reality system is explored for applications in urban environments. We formulate a new objective function which combines the point reconstruction errors and constraints on spatial point distribution. Based on this formulation, a mixed integer programming scheme is utilized to solve the points reduction problem. The mobile augmented reality system explored in this paper is composed of the offline and online stages. At the offline stage, we build up the localization database using structure from motion and compress the point cloud by the proposed point cloud reduction method. While at the online stage, we compute the camera pose in real time by combining an image-based localization algorithm and a continuous pose tracking algorithm. Experimental results on benchmark and real data show that compared with the existing methods, this geometry-based point cloud reduction method selects a point cloud subset which helps the image-based localization method to achieve higher success rate. Also, the experiments conducted on a mobile platform show that the reduced point cloud not only reduces the time consuming for initialization and re-initialization, but also makes the memory footprint small, resulting a scalable and real-time mobile augmented reality system.

THE APPLICATION OF AUGMENTED REALITY IN MARKETING

On the basis of the analysis of the source literature, the article tackled the subject of Augmented Reality as a modern marketing tool. To begin with, the presumptions were diagnosed which constitute the proof of the increasing significance of this technology. Then it Was defined what Augmented Reality is, as well as its functionality Was presented. In the further part of the text, the selected examples of the practical application of AR, as well as their usage in marketing activity, were provided. Moreover, a case study Was presented in which the application of Mobile Augmented Reality Systems (MARS) Was discussed in a broader way on the example of mobile applications. The article concludes with a vision of the further development of Augmented Reality in the marketing aspect

Analysis of the Technology Acceptance Theoretical Model in Examining Users’ Behavioural Intention to Use an Augmented Reality App (IMAPCampus)

As technology penetrates into our lives, the vital need for institutions to provide rapid access to information has grown. Recently, Augmented Reality (AR) has emerged as a technology for educational institutions to enhance users’ experience by overlaying computational information into their reality. iMAP_CampUS is a mobile AR application showing campus-related information superimposed on a map of Macquarie University. Using iMAP_CampUS app, our goal is to investigate the factors influencing the acceptance of a typical mobile AR system. The thesis proposes a theoretical framework with 14 research hypotheses based on UTAUT, IS success factors and Motivation theory. This framework is empirically examined using web-based survey data from a sample of 86 users. We use Structural Equation Modeling (SEM) and Partial Least Squares (PLS) to evaluate the acceptance and behavioural intention to use iMAP-CampUS app. The results indicate that ten research hypotheses have been significantly supported, while four have been rejected. The findings state that perceived enjoyment and user's satisfaction are important determinants for the use of iMap-CampUS. However, performance expectancy has not demonstrated any significant impacts on behavioural intention to use the app.

Fieldwork in Geosciences assisted by ARGeo: A mobile Augmented Reality system

Gathering data on the field is a crucial task in many disciplines. Moreover, in the Geosciences the GPS positioning is relevant to the data acquisition as well as to the planning of the fieldwork. Nowadays, mobile devices are widespread, constituting an accessible platform consisting of single devices coupled with different sensors for data acquisition, such as GPS, compass, magnetometer, etc. Emerging technologies such as Augmented Reality (AR) enable the use of these devices as a software platform to complement the perception of our surrounding environment. Despite the fact that there are several AR applications focused on different aspects of Geosciences, a comprehensive fieldwork oriented system, which can be easily adapted to the community needs, is still missing. Based on a multidisciplinary work between professionals from Geosciences and Computer Sciences, we designed and developed a framework based AR system named ARGeo. The proposed system constitutes a complementing tool for the geologist's fieldwork carefully designed to be used in remote sites, using only the mobile device hardware and without the need of an internet connection for data acquisition.ARGeo complements the fieldwork observation and the precise recording of geological data needed, e.g., for the interpretation of folded structures. It allows the user to register geo-tagged information such as points of interests (i.e. references on the field or the fold itself) using natural interactions. In addition, it provides two novel features: an interactive dipping plane measurement from distant points of view and a back-in-time visualization of previous recorded positions, in order to help understanding the spatial relations among the recorded samples. Pilot studies were conducted with domain experts of geology and they agree on the potential of the system. Results point out that ARGeo naturally integrates mobile devices and AR to the geologists' fieldwork. Its possible extension with new features to the Geosciences as well as to other application fields is detailed.

A Systematic Review of Learning Through Mobile Augmented Reality

&lt;p&gt;In the beginning of 2000, researchers started to see the potential of using Augmented Reality (AR) in educational and foresaw that further research within the field. Since then, AR research have taken many different approaches. This is also true for AR in relation to pedagogical purposes. This study is to investigate what has been studied within the AR field related to mobile augmented reality. It attempts to make systematic review of how learning and pedagogical aspects have been approached in the articles. In recent years, mobile augmented reality has become increasingly interesting due to the mobile devices small form factors and their ability to let the students move around freely while learning. The aim of this study is to make a systematic review of pedagogical uses of mobile augmented reality. Based on a review of previous literature of mobile AR systems for pedagogical purposes, published between 2000-2017, make it possible to see in which direction mobile AR systems for education are heading and how future mobile AR systems should be designed to best fit the needs of future students so they can more effectively improve their learning.&lt;/p&gt;

Augmented Reality Applied in Dietary Monitoring

Abstract Recent advances in augmented reality (AR) have attracted much attention in nutrition and healthcare education. In the context of obtaining dietary knowledge, a mobile AR system was developed for learning and exploration, which allowed students to scan food images, receive information about nutrient content and record as well as accumulate daily nutrient intake. Students could also access learning materials provided in the system to achieve the learning objectives. Their learning outcomes were gathered at the close, with reactions to the learning experiences also assessed via a set of questionnaire items (using a 5 point Likert scale) in various criteria. Both qualitative and quantitative data were gathered, showing that most students achieved the learning objectives and were positive about exploring with AR. The results of this study indicated that students with high levels of monitoring had better learning outcomes (p&lt;0.05) and were more positive about the varied criteria in their responses, including: visual interest and learning enjoyment, functional use, personal relevance and learning of knowledge (p&lt;0.05). The effect of the self-participatory aspect of AR on learning is emphasized.