A Review on Mixed Reality: Current Trends, Challenges and Prospects

Self Cite

Most existing augmented reality (AR) applications are suitable for cases in which only a small number of real world entities are involved, such as superimposing a character on a single surface. In this case, we only need to calculate pose of the camera relative to that surface. However, when an AR health or environmental application involves a one-to-one relationship between an entity in the real-world and the corresponding object in the computer model (geo-referenced object), we need to estimate the pose of the camera in reference to a common coordinate system for better geo-referenced object registration in the real-world. New innovations in developing cheap sensors, computer vision techniques, machine learning, and computing power have helped to develop applications with more precise matching between a real world and a virtual content. AR Tracking techniques can be divided into two subcategories: marker-based and marker-less approaches. This paper provides a comprehensive overview of marker-less registration and tracking techniques and reviews their most important categories in the context of ubiquitous Geospatial Information Systems (GIS) and AR focusing to health and environmental applications. Basic ideas, advantages, and disadvantages, as well as challenges, are discussed for each subcategory of tracking and registration techniques. We need precise enough virtual models of the environment for both calibrations of tracking and visualization. Ubiquitous GISs can play an important role in developing AR in terms of providing seamless and precise spatial data for outdoor (e.g., environmental applications) and indoor (e.g., health applications) environments.

Section: No-model-based Trackingmentioning

confidence: 99%

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems

Sadeghi‐Niaraki

Choi

2020

Self Cite

“…The latter can help users improve their performance in many tasks by providing pertinent information about the pictured scenario. Mixed reality (MR) extends the concept of AR with features to detect changes in the real world, allowing the virtual elements to react and adapt, e.g., by simulating the collision of a virtual ball with a real wall [ 4 ]. VR, AR, and MR are represented by Milgram and Kishino through a virtuality continuum diagram [ 5 ], presented in Figure 1 .…”

Section: Introductionmentioning

confidence: 99%

Web AR Solution for UAV Pilot Training and Usability Testing

Ribeiro

Ramos

Safadinho

et al. 2021

Data and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.

“…In the viewpoint of the safety and comfort of smart glasses, there are several issues such as weight [48,49], battery [50,51], AR/VR [52][53][54], and heat [31,33]. In Reference [48], regarding weight issues, the effect of weight balance for shutter glasses in terms of subjective discomfort and physical load on the nose has been investigated [48] and a user discomfort on the different wearing mode glasses with different support points has been presented [49].…”

Section: Introductionmentioning

confidence: 99%

“…With respect to battery safety, an extremely safe and wearable solid-state zinc ion battery has been fabricated [50] and a quasi-solid-state aqueous rechargeable lithium-ion battery with outstanding stability, flexibility, safety, and breathability toward various wearable electronics has been reported [51]. AR/VR include many problems such as display size, resolution, computing capability, negative effects in some people with autism spectrum disorder, and architecture/server/network issues [52][53][54]. Moreover, it is necessary to ensure the safety and comfort due to heat generation [31,33] since smart glasses are worn on the face/head of the human body for use.…”

Section: Introductionmentioning

confidence: 99%

Thermal Model and Countermeasures for Future Smart Glasses

Matsuhashi

Kanamoto

Kurokawa

2020

The market for wearable devices such as smart watches and smart glasses continues to grow rapidly. Smart glasses are attracting particular attention because they offer convenient features such as hands-free augmented reality (AR). Since smart glasses directly touch the face and head, the device with high temperature has a detrimental effect on human physical health. This paper presents a thermal network model in a steady state condition and thermal countermeasure methods for thermal management of future smart glasses. It is accomplished by disassembling the state by wearing smart glasses into some parts, creating the equivalent thermal resistance circuit for each part, approximating heat-generating components such as integrated circuits (ICs) to simple physical structures, setting power consumption to the heat sources, and providing heat transfer coefficients of natural convection in air. The average temperature difference between the thermal network model and a commercial thermal solver is 0.9 °C when the maximum temperature is 62 °C. Results of an experiment using the model show that the temperature of the part near the ear that directly touches the skin can be reduced by 51.4% by distributing heat sources into both sides, 11.1% by placing higher heat-generating components farther from the ear, and 65.3% in comparison with all high conductivity materials by using a combination of low thermal conductivity materials for temples and temple tips and high conductivity materials for rims.