An Intelligent Boxing Application through Augmented Reality for two users – Human Computer Interaction attempt.

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

Recupera algunos de los elementos menos estudiados y reconocidos en el ensayo latinoamericano: su profunda vocación de reflexión, diálogo y mediación intelectual; su plasticidad y apertura a la búsqueda del sentido; su vínculo con la sociabilidad, la conversación y la generación de un espacio simbólico de encuentro; su capa cidad de establecer una nueva retroalimentación entre lectura y escritura.

Three-dimensional sound's effectiveness in virtual reality (VR) environments has been widely studied. However, due to the big differences between VR and augmented reality (AR) systems in registration, calibration, perceptual difference of immersiveness, navigation, and localization, it is important to develop new approaches to seamlessly register virtual 3-D sound in AR environments and conduct studies on 3-D sound's effectiveness in AR context. In this paper, we design two experimental AR environments to study the effectiveness of 3-D sound both quantitatively and qualitatively. Two different tracking methods are applied to retrieve the 3-D position of virtual sound sources in each experiment. We examine the impacts of 3-D sound on improving depth perception and shortening task completion time. We also investigate its impacts on immersive and realistic perception, different spatial objects identification, and subjective feeling of human presence and collaboration. Our studies show that applying 3-D sound is an effective way to complement visual AR environments. It helps depth perception and task performance, and facilitates collaborations between users. Moreover, it enables a more realistic environment and more immersive feeling of being inside the AR environment by both visual and auditory means. In order to make full use of the intensity cues provided by 3-D sound, a process to scale the intensity difference of 3-D sound at different depths is designed to cater small AR environments. The user study results show that the scaled 3-D sound significantly increases the accuracy of depth judgments and shortens the searching task completion time. This method provides a necessary foundation for implementing 3-D sound in small AR environments. Our user study results also show that this process does not degrade the intuitiveness and realism of an augmented audio reality environment

Introduction: Augmented Reality (AR) systems are systems in which users view and interact with virtual objects overlaying the real world. AR systems are used across a variety of disciplines, i.e., games, medicine, and education to name a few. Optical See-Through (OST) AR displays allow users to perceive the real world directly by combining computer-generated imagery overlaying the real world. While perception of depth and visibility of objects is a widely studied field, we wanted to observe how color, luminance, and movement of an object interacted with each other as well as external luminance in OST AR devices. Little research has been done regarding the issues around the effect of virtual objects’ parameters on depth perception, external lighting, and the effect of an object’s mobility on this depth perception.Methods: We aim to perform an analysis of the effects of motion cues, color, and luminance on depth estimation of AR objects overlaying the real world with OST displays. We perform two experiments, differing in environmental lighting conditions (287 lux and 156 lux), and analyze the effects and differences on depth and speed perceptions.Results: We have found that while stationary objects follow previous research with regards to depth perception, motion and both object and environmental luminance play a factor in this perception.Discussion: These results will be significantly useful for developers to account for depth estimation issues that may arise in AR environments. Awareness of the different effects of speed and environmental illuminance on depth perception can be utilized when performing AR or MR applications where precision matters.

Augmented reality sickness questionnaire (ARSQ): A refined questionnaire for augmented reality environment

Augmented Reality (AR), the overlay of virtual images onto the real world, is an increasingly popular technique for developing new human-computer interfaces. As human navigation and orientation in different environments depend on both visual and auditory information, sound plays a very important role in AR applications. In this paper we explore users' capability to localize a spatial sound (registered with a virtual object) in an AR environment, under different spatial configurations of the virtual scene. The results not only confirm several previous findings on sound localization, but also point out some important new visual-audio cues which should be taken into consideration for effective localization and orientation in AR environment. Finally, this paper provides tentative guidelines for adding spatial sound to AR environments.

Augmented Reality (AR) is a rapidly evolving technology that overlays digital information onto the real world, enhancing user interaction and perception.This survey provides a comprehensive review of AR technologies, development frameworks, application domains, challenges, and future research directions.We discuss the fundamental components of AR systems, including hardware and software architectures, tracking and registration methods, and user interaction techniques.Furthermore, we explore various AR applications across industries such as healthcare, education, gaming, and manufacturing.Finally, we highlight key challenges and future opportunities in AR research, including AI integration, AR cloud, and ethical considerations.

There is a growing interest for the broad use of Augmented Reality (AR) and Virtual Reality (VR) in the fields of bioinformatics and cheminformatics to visualize complex biological and chemical structures. AR and VR technologies allow for stunning and immersive experiences, offering untapped opportunities for both research and education purposes. However, preparing 3D models ready to use for AR and VR is time-consuming and requires a technical expertise that severely limits the development of new contents of potential interest for structural biologists, medicinal chemists, molecular modellers and teachers. Herein we present the RealityConvert software tool and associated website, which allow users to easily convert molecular objects to high quality 3D models directly compatible for AR and VR applications. For chemical structures, in addition to the 3D model generation, RealityConvert also generates image trackers, useful to universally call and anchor that particular 3D model when used in AR applications. The ultimate goal of RealityConvert is to facilitate and boost the development and accessibility of AR and VR contents for bioinformatics and cheminformatics applications. http://www.realityconvert.com. dfourch@ncsu.edu. Supplementary data are available at Bioinformatics online.

Virtual characters are now widely used in games, computer-generated (CG) movies, virtual reality (VR), and communication media. The continued technological innovations in motion capture mean that a more natural representation of a three-dimensional character’s motion should be achievable. Many researchers have investigated how virtual characters interact with their surrounding environment through spatial relationships, which were introduced for adapting and preserving character motion. However, technical problems should be resolved to enable the control of characters in augmented reality (AR) environments that combine with the real world, and this can be achieved by adapting motion to environmental differences using original motion datasets. In this paper, we investigate a novel method for preserving automatic motion adaptation for a virtual character in AR environments. We used specific object (e.g., puddle) recognition and the spatial properties of the user’s surrounding space, e.g., object types and positions, and ran validation experiments to provide accurate motion to improve the AR experience. Our experimental study showed positive results in terms of smooth motion in AR configurations. We also found that the participants using AR felt a greater sense of co-presence with the character through adapted motion.

The combination of technology Augmented Reality (AR) with educational content aims to create new ideas that can improve the effectiveness and attractiveness of teaching and learning for students in real-life scenarios. The use of AR technology can make theprocess of teaching and learning more enjoyable, in which students' interest in learning can be stimulated. The AR technology has three characteristics. The first feature is that AR technology is a combination of virtual objects with the real world. The second feature is that AR operates in real time and interactively. The last feature is that it has 3 dimensions (3D) for virtual objects. In this study, the ADDIE model includes five phases, namely Analysis, Design, Development, Implementation and Evaluation, which are utilised to develop applications based on AR technology in education for the topic of Current and Voltage Division. To identify the effectiveness of the application of AR technology, a survey using questionnaire was conducted among pre-serviceteachers to know their perceptions of the development of AR applications namely as Voltrent AR. As this is a quantitative study where questionnaires were distributed to 73 students from the class of Bachelor of Technology with Education (Electric and Electronics) with Honours and Bachelor of Technology with Education (Living Skills) with Honours at Universiti Teknologi Malaysia (UTM) Skudai, Johor. Most respondents gave very positive feedback on the use of AR in education, especially for the topic of Current and Voltage Division. AR is viewed as a medium of instruction that is innovative, interesting and effective. Voltrent AR application development is successfully developed based on the ADDIE model, and the application development of the constructivism theory was applied in this AR application. Thus, the AR application development has reached the desired objective of producing application-based Augmented Reality as a teaching aid.

ABSTRACTPainting is a complex and creative process that involves the use of various drawing skills to create artworks. The concept of training artificial intelligence models to imitate this process is referred to as neural painting. To enable ordinary people to engage in the process of painting, we propose PainterAR, a novel interface that renders any paintings stroke‐by‐stroke in an immersive and realistic augmented reality (AR) environment. PainterAR is composed of two components: the neural painting model and the AR interface. Regarding the neural painting model, unlike previous models, we introduce the Kullback–Leibler divergence to replace the original Wasserstein distance existed in the baseline paint transformer model, which solves an important problem of encountering different scales of strokes (big or small) during painting. We then design an interactive AR interface, which allows users to upload an image and display the creation process of the neural painting model on the virtual drawing board. Experiments demonstrate that the paintings generated by our improved neural painting model are more realistic and vivid than previous neural painting models. The user study demonstrates that users prefer to control the painting process interactively in our AR environment.

Augmented reality (AR) applications that overlay the perception of the real world with digitally generated information are on the cusp of commercial viability. AR has appeared in several commercial platforms like Microsoft HoloLens and smartphones. They extend the user experience beyond two dimensions and supplement the normal 3D world of a user. A typical location-based multi-player AR application works through a three-step process, wherein the system collects sensory data from the real world, identifies objects based on their context, and finally, renders information on top of senses of a user. However, because these AR applications frequently exchange data with users, they have exposed new individual and public safety issues. In this paper, we develop ARSpy, a user location tracking system solely based on network traffic information of the user, and we test it on location-based multi-player AR applications. We demonstrate the effectiveness and efficiency of the proposed scheme via real-world experiments on 12 volunteers and show that we could obtain the geolocation of any target with high accuracy. We also propose three mitigation methods to mitigate these side channel attacks. Our results reveal a potential security threat in current location-based multi-player AR applications and serve as a critical security reminder to a vast number of AR users.

Mobile Augmented Reality (AR) applications allow the user to interact with virtual objects positioned within the real world via a smart phone, tablet or smart glasses. As the popularity of these applications grows, recent researchers have identified several security and privacy issues pertaining to the collection and storage of sensitive data from device sensors. Location-based AR applications typically not only collect user location data, but transmit it to a remote server in order to download nearby virtual content. In this paper we show that the pattern of network traffic generated by this process alone can be used to infer the user's location. We demonstrate a side-channel attack against a widely available Mobile AR application inspired by Website Fingerprinting methods. Through the strategic placement of virtual content and prerecording of the network traffic produced by interacting with this content, we are able to identify the location of a user within the target area with an accuracy of 94%. This finding reveals a previously unexplored vulnerability in the implementation of Mobile AR applications and we offer several recommendations to mitigate this threat.

Augmented reality technologies undertake focus role which provide opportunity to harmonize the earthilyreality with virtual field and evaluate their integral elements.The very first examples of augmented realityapplications are viewers on the head,simulators,wearable tools,pocket PCs,desktop PCs and cameras whichare integrated externally but augmented reality applications have gain a great acceleration by developingtechnologies such as internet,becoming popular for the mobile devices and their mobile applicationsaccordingly and especially by the appearance of the smart wears and increase on their functions.Augmentedreality applications that are often used in defence,industry,medicine,trade and entertainment are now startedto be used in the education.Augmented reality applications achieve deep learning of the systems or objectswhich are hard to learn by attracting attention and cares of the students by providing their different viewsduring teaching and learning process.Also these applications supports students to use their creativity byexpanding their imagination.Especially if we consider today’s students are digital natives(Y and Z generation) who grow up in the multimedia world and inside the technology,it is a reality that augmented reality applications which have rich content in the learning-teaching environments can have a role that increase themotivations of the students instead of a classic course book. In the light of these information, in this study theresearch and application samples of augmented reality which is now used widely in teaching and learningprocess the effect of augmented reality on teaching and learning is handled.Keywords: Augmented reality, augmented reality applications in education

Controlling assistive robots can be challenging for some users, especially those lacking relevant experience. Augmented Reality (AR) User Interfaces (UIs) have the potential to facilitate this task. Although extensive research regarding legged manipulators exists, comparatively little is on their UIs. Most existing UIs leverage traditional control interfaces such as joysticks, Hand-Held (HH) controllers and 2D UIs. These interfaces not only risk being unintuitive, thus discouraging interaction with the robot partner, but also draw the operator’s focus away from the task and towards the UI. This shift in attention raises additional safety concerns, particularly in potentially hazardous environments where legged manipulators are frequently deployed. Moreover, traditional interfaces limit the operators’ availability to use their hands for other tasks. Towards overcoming these limitations, in this article, we provide a user study comparing an AR Head-Mounted Display (HMD) UI we developed for controlling a legged manipulator against off-the-shelf control methods for such robots. This user study involved 27 participants and 135 trials, from which we gathered over 405 completed questionnaires. These trials involved multiple navigation and manipulation tasks with varying difficulty levels using a Boston Dynamics’s Spot, a 7 df Kinova robot arm and a Robotiq 2F-85 gripper that we integrated into a legged manipulator. We made the comparison between UIs across multiple dimensions relevant to a successful human–robot interaction. These dimensions include cognitive workload, technology acceptance, fluency, system usability, immersion and trust. Our study employed a factorial experimental design with participants undergoing five different conditions, generating longitudinal data. Due to potential unknown distributions and outliers in such data, using parametric methods for its analysis is questionable, and while non-parametric alternatives exist, they may lead to reduced statistical power. Therefore, to analyse the data that resulted from our experiment, we chose Bayesian data analysis as an effective alternative to address these limitations. Our results show that AR UIs can outpace HH-based control methods and reduce the cognitive requirements when designers include hands-free interactions and cognitive offloading principles into the UI. Furthermore, the use of the AR UI together with our cognitive offloading feature resulted in higher usability scores and significantly higher fluency and Technology Acceptance Model scores. Regarding immersion, our results revealed that the response values for the AR Immersion questionnaire associated with the AR UI are significantly higher than those associated with the HH UI, regardless of the main interaction method with the former, i.e., hand gestures or cognitive offloading. Derived from the participants’ qualitative answers, we believe this is due to a combination of factors, of which the most important is the free use of the hands when using the HMD, as well as the ability to see the real environment without the need to divert their attention to the UI. Regarding trust, our findings did not display discernible differences in reported trust scores across UI options. However, during the manipulation phase of our user study, where participants were given the choice to select their preferred UI, they consistently reported higher levels of trust compared to the navigation category. Moreover, there was a drastic change in the percentage of participants that selected the AR UI for completing this manipulation stage after incorporating the cognitive offloading feature. Thus, trust seems to have mediated the use and non-use of the UIs in a dimension different from the ones considered in our study, i.e., delegation and reliance. Therefore, our AR HMD UI for the control of legged manipulators was found to improve human–robot interaction across several relevant dimensions, underscoring the critical role of UI design in the effective and trustworthy utilisation of robotic systems.