41,255 research outputs found

    Smartphone app with usage of AR technologies - SolAR System

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    The article describes the AR mobile system for Sun system simulation. The main characteristics of AR systems architecture are given. The differences between tracking and without tracking technics are underlined. The architecture of the system of use of complemented reality for the study of astronomy is described. The features of the system and the principles of its work are determined.Comment: 6 pages,9 figure

    CloudAR: A Cloud-based Framework for Mobile Augmented Reality

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    Computation capabilities of recent mobile devices enable natural feature processing for Augmented Reality (AR). However, mobile AR applications are still faced with scalability and performance challenges. In this paper, we propose CloudAR, a mobile AR framework utilizing the advantages of cloud and edge computing through recognition task offloading. We explore the design space of cloud-based AR exhaustively and optimize the offloading pipeline to minimize the time and energy consumption. We design an innovative tracking system for mobile devices which provides lightweight tracking in 6 degree of freedom (6DoF) and hides the offloading latency from users' perception. We also design a multi-object image retrieval pipeline that executes fast and accurate image recognition tasks on servers. In our evaluations, the mobile AR application built with the CloudAR framework runs at 30 frames per second (FPS) on average with precise tracking of only 1~2 pixel errors and image recognition of at least 97% accuracy. Our results also show that CloudAR outperforms one of the leading commercial AR framework in several performance metrics

    Interaction Methods for Smart Glasses

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    Since the launch of Google Glass in 2014, smart glasses have mainly been designed to support micro-interactions. The ultimate goal for them to become an augmented reality interface has not yet been attained due to an encumbrance of controls. Augmented reality involves superimposing interactive computer graphics images onto physical objects in the real world. This survey reviews current research issues in the area of human computer interaction for smart glasses. The survey first studies the smart glasses available in the market and afterwards investigates the interaction methods proposed in the wide body of literature. The interaction methods can be classified into hand-held, touch, and touchless input. This paper mainly focuses on the touch and touchless input. Touch input can be further divided into on-device and on-body, while touchless input can be classified into hands-free and freehand. Next, we summarize the existing research efforts and trends, in which touch and touchless input are evaluated by a total of eight interaction goals. Finally, we discuss several key design challenges and the possibility of multi-modal input for smart glasses

    Towards Quality of Experience Determination for Video in Augmented Binocular Vision Scenarios

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    With the continuous growth in the consumer markets of mobile smartphones and increasingly in augmented reality wearable devices, several avenues of research investigate the relationships between the quality perceived by mobile users and the delivery mechanisms at play to support a high quality of experience for mobile users. In this paper, we present the first study that evaluates the relationships of mobile movie quality and the viewer-perceived quality thereof in an augmented reality setting with see-through devices. We find that participants tend to overestimate the video quality and exhibit a significant variation of accuracy that leans onto the movie content and its dynamics. Our findings, thus, can broadly impact future media adaptation and delivery mechanisms for this new display format of mobile multimedia.Comment: Accepted to Signal Processing: Image Communicatio

    An Improved Tracking using IMU and Vision Fusion for Mobile Augmented Reality Applications

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    Mobile Augmented Reality (MAR) is becoming an important cyber-physical system application given the ubiquitous availability of mobile phones. With the need to operate in unprepared environments, accurate and robust registration and tracking has become an important research problem to solve. In fact, when MAR is used for tele-interactive applications involving large distances, say from an accident site to insurance office, tracking at both the ends is desirable and further it is essential to appropriately fuse inertial and vision sensors data. In this paper, we present results and discuss some insights gained in marker-less tracking during the development of a prototype pertaining to an example use case related to breakdown or damage assessment of a vehicle. The novelty of this paper is in bringing together different components and modules with appropriate enhancements towards a complete working system

    Mobile Head Tracking for eCommerce and Beyond

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    Shopping is difficult for people with motor impairments. This includes online shopping. Proprietary software can emulate mouse and keyboard via head tracking. However, such a solution is not common for smartphones. Unlike desktop and laptop computers, they are also much easier to carry indoors and outdoors.To address this, we implement and open source button that is sensitive to head movements tracked from the front camera of iPhone X. This allows developers to integrate in eCommerce applications easily without requiring specialized knowledge. Other applications include gaming and use in hands-free situations such as during cooking, auto-repair. We built a sample online shopping application that allows users to easily browse between items from various categories and take relevant action just by head movements. We present results of user studies on this sample application and also include sensitivity studies based on two independent tests performed at 3 different distances to the screen.Comment: 10 pages, 5 figure

    A Low Cost Vision Based Hybrid Fiducial Mark Tracking Technique for Mobile Industrial Robots

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    The field of robotic vision is developing rapidly. Robots can react intelligently and provide assistance to user activities through sentient computing. Since industrial applications pose complex requirements that cannot be handled by humans, an efficient low cost and robust technique is required for the tracking of mobile industrial robots. The existing sensor based techniques for mobile robot tracking are expensive and complex to deploy, configure and maintain. Also some of them demand dedicated and often expensive hardware. This paper presents a low cost vision based technique called Hybrid Fiducial Mark Tracking (HFMT) technique for tracking mobile industrial robot. HFMT technique requires off-the-shelf hardware (CCD cameras) and printable 2-D circular marks used as fiducials for tracking a mobile industrial robot on a pre-defined path. This proposed technique allows the robot to track on a predefined path by using fiducials for the detection of Right and Left turns on the path and White Strip for tracking the path. The HFMT technique is implemented and tested on an indoor mobile robot at our laboratory. Experimental results from robot navigating in real environments have confirmed that our approach is simple and robust and can be adopted in any hostile industrial environment where humans are unable to work.Comment: 6 pages, 7 figure

    Vision-based Pose Estimation for Augmented Reality : A Comparison Study

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    Augmented reality aims to enrich our real world by inserting 3D virtual objects. In order to accomplish this goal, it is important that virtual elements are rendered and aligned in the real scene in an accurate and visually acceptable way. The solution of this problem can be related to a pose estimation and 3D camera localization. This paper presents a survey on different approaches of 3D pose estimation in augmented reality and gives classification of key-points-based techniques. The study given in this paper may help both developers and researchers in the field of augmented reality.Comment: IEEE International Conference on Pattern Analysis and Intelligent Systems PAIS'201

    Virtual Reality based Learning Systems

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    This article is based on studies of the existing literature, focusing on the states-of-the-arts on virtual reality (VR) and its potential uses in learning. Different platforms have been used to improve the learning effects of VR that offers exciting opportunities in various fields. As more and more students want in a distance, part-time, or want to continue their education, VR has attracted considerable attention in learning, training, and traditional education. VR based learning enables operators to bring together all disciplinary resources in a common playground. The VR base multimedia platform has successfully demonstrated great potential of education and training. In this paper, we will discuss existing systems and their uses and address the technical challenges and future directions.Comment: Computer Communication Technology, 201

    Artificial Intelligence Assisted Infrastructure Assessment Using Mixed Reality Systems

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    Conventional methods for visual assessment of civil infrastructures have certain limitations, such as subjectivity of the collected data, long inspection time, and high cost of labor. Although some new technologies i.e. robotic techniques that are currently in practice can collect objective, quantified data, the inspectors own expertise is still critical in many instances since these technologies are not designed to work interactively with human inspector. This study aims to create a smart, human centered method that offers significant contributions to infrastructure inspection, maintenance, management practice, and safety for the bridge owners. By developing a smart Mixed Reality framework, which can be integrated into a wearable holographic headset device, a bridge inspector, for example, can automatically analyze a certain defect such as a crack that he or she sees on an element, display its dimension information in real-time along with the condition state. Such systems can potentially decrease the time and cost of infrastructure inspections by accelerating essential tasks of the inspector such as defect measurement, condition assessment and data processing to management systems. The human centered artificial intelligence will help the inspector collect more quantified and objective data while incorporating inspectors professional judgement. This study explains in detail the described system and related methodologies of implementing attention guided semi supervised deep learning into mixed reality technology, which interacts with the human inspector during assessment. Thereby, the inspector and the AI will collaborate or communicate for improved visual inspection.Comment: 5,240 word texts, 3 tables, 14 figures. Transportation Research Record: Journal of the Transportation Research Board, 201
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