Search Results (8)

Recently, in the field of Virtual Reality (VR), cloud VR has been proposed as a method to address issues related to the performance and portability of Head-Mounted Displays (HMD). Cloud VR offers advantages such as lightweight HMD, telepresence, and mobility. However, issues such as Motion-To-Photon (MTP) latency and the handling of large-scale traffic due to continuous video streaming persist. Utilizing edge computing is considered a potential solution for some of these issues. Nevertheless, providing this in a cloud–edge continuum environment for simultaneous users presents additional issues, such as server rendering load and multi-user MTP latency threshold. This study proposes an adaptive MicroServices Architecture (MSA) and a service orchestration based on it to effectively provide multi-user cloud VR in a cloud–edge continuum environment. The proposed method aims to ensure the MTP latency threshold for each user while addressing network congestion, even when the application is provided to multiple users simultaneously in a resource-constrained edge network environment. Furthermore, it aims to maintain high edge applicability for microservices through efficient edge resource management. Simulation results confirm that the proposed method demonstrates better performance in terms of networking and MTP latency compared to other edge resource-management methods. Full article

Cloud virtual reality (VR) is attracting attention in terms of its lightweight head-mounted display (HMD), providing telepresence and mobility. However, it is still in the research stages due to motion-to-photon (MTP) latency, the need for high-speed network infrastructure, and large-scale traffic processing problems. These problems are expected to be partially solved through edge computing, but the limited computing resource capacity of the infrastructure presents new challenges. In particular, in order to efficiently provide multi-user content such as remote meetings on edge devices, resource provisioning is needed that considers the application’s traffic patterns and computing resource requirements at the same time. In this study, we present a microservice architecture (MSA)-based application to provide multi-user cloud VR in edge computing and propose a scheme for planning an efficient service deployment considering the characteristics of each service. The proposed scheme not only guarantees the MTP latency threshold for all users but also aims to reduce networking and computing resource waste. The proposed scheme was evaluated by simulating various scenarios, and the results were compared to several studies. It was confirmed that the proposed scheme represents better performance metrics than the comparison schemes in most cases from the perspectives of networking, computing, and MTP latency. Full article

The growing interest in augmented reality applications has led to an in-depth look at the performance of head-mounted displays and their testing in numerous domains. Other devices for augmenting the real world with virtual information are presented less frequently and usually focus on the description of the device rather than on its performance analysis. This is the case of projected augmented reality, which, compared to head-worn AR displays, offers the advantages of being simultaneously accessible by multiple users whilst preserving user awareness of the environment and feeling of immersion. This work provides a general evaluation of a custom-made head-mounted projector for the aid of precision manual tasks through an experimental protocol designed for investigating spatial and temporal registration and their combination. The results of the tests show that the accuracy ($0.6\pm 0.1$ mm of spatial registration error) and motion-to-photon latency ($113\pm 12$ ms) make the proposed solution suitable for guiding precision tasks. Full article

The utilization of commercially available virtual reality (VR) environments has increased over the last decade. Motion sickness that is commonly reported while using VR devices is still prevalent and reported at a higher than acceptable rate. The virtual reality induced symptoms and effects (VRISE) are considered the largest barrier to widespread usage. Current measurement methods have uniform use across studies but are subjective and are not designed for VR. VRISE and other motion sickness symptom profiles are similar but not exactly the same. Common objective physiological and biomechanical as well as subjective perception measures correlated with VRISE should be used instead. Many physiological biomechanical and subjective changes evoked by VRISE have been identified. There is a great difficulty in claiming that these changes are directly caused by VRISE due to numerous other factors that are known to alter these variables resting states. Several theories exist regarding the causation of VRISE. Among these is the sensory conflict theory resulting from differences in expected and actual sensory input. Reducing these conflicts has been shown to decrease VRISE. User characteristics contributing to VRISE severity have shown inconsistent results. Guidelines of field of view (FOV), resolution, and frame rate have been developed to prevent VRISE. Motion-to-photons latency movement also contributes to these symptoms and effects. Intensity of content is positively correlated to VRISE, as is the speed of navigation and oscillatory displays. Duration of immersion shows greater VRISE, though adaptation has been shown to occur from multiple immersions. The duration of post immersion VRISE is related to user history of motion sickness and speed of onset. Cognitive changes from VRISE include decreased reaction time and eye hand coordination. Methods to lower VRISE have shown some success. Postural control presents a potential objective variable for predicting and monitoring VRISE intensity. Further research is needed to lower the rate of VRISE symptom occurrence as a limitation of use. Full article

One of the most frequent technical factors affecting Virtual Reality (VR) performance and causing motion sickness is system latency. In this paper, we adopted predictive algorithms (i.e., Dead Reckoning, Kalman Filtering, and Deep Learning algorithms) to reduce the system latency. Cubic, quadratic, and linear functions are used to predict and curve fitting for the Dead Reckoning and Kalman Filtering algorithms. We propose a time series-based LSTM (long short-term memory), Bidirectional LSTM, and Convolutional LSTM to predict the head and body motion and reduce the motion to photon latency in VR devices. The error between the predicted data and the actual data is compared for statistical methods and deep learning techniques. The Kalman Filtering method is suitable for predicting since it is quicker to predict; however, the error is relatively high. However, the error property is good for the Dead Reckoning algorithm, even though the curve fitting is not satisfactory compared to Kalman Filtering. To overcome this poor performance, we adopted deep-learning-based LSTM for prediction. The LSTM showed improved performance when compared to the Dead Reckoning and Kalman Filtering algorithm. The simulation results suggest that the deep learning techniques outperformed the statistical methods in terms of error comparison. Overall, Convolutional LSTM outperformed the other deep learning techniques (much better than LSTM and Bidirectional LSTM) in terms of error. Full article

Because the interest in virtual reality (VR) has increased recently, studies on head-mounted displays (HMDs) have been actively conducted. However, HMD causes motion sickness and dizziness to the user, who is most affected by motion-to-photon latency. Therefore, equipment for measuring and quantifying this occurrence is very necessary. This paper proposes a novel system to measure and visualize the time sequential motion-to-photon latency in real time for HMDs. Conventional motion-to-photon latency measurement methods can measure the latency only at the beginning of the physical motion. On the other hand, the proposed method can measure the latency in real time at every input time. Specifically, it generates the rotation data with intensity levels of pixels on the measurement area, and it can obtain the motion-to-photon latency data in all temporal ranges. Concurrently, encoders measure the actual motion from a motion generator designed to control the actual posture of the HMD device. The proposed system conducts a comparison between two motions from encoders and the output image on a display. Finally, it calculates the motion-to-photon latency for all time points. The experiment shows that the latency increases from a minimum of 46.55 ms to a maximum of 154.63 ms according to the workload levels. Full article

This paper proposes a novel tangible interface system to enhance the immersive experience in virtual reality environments. The proposed system allows representing physical properties of the tool, such as the deflection of the elastic rods, which users handle in a virtual and physical environment. This system is composed of two parts; one is an articulated interface to visually represent the physical behavior and the other is a computational algorithm that can compute a set of 6-DOF positions of the links. The proposed computational algorithm extends an active contour model, which is used primarily in computer vision and image processing, incorporating a spring and damping constraint energy functional. An elastic rod is modeled as a series of rigid line segments with a symmetric relationship between neighboring segments, and its shape is modeled to be influenced by energies that are induced by a user, and the external deformation of the spline. The symmetric and sparse properties of the proposed model enable an efficient energy minimization process, and the modification of a number of the line segments. Based on this configuration, we construct an energy generation method based on the positional displacement of the base element to generate the deflection behavior of the contour according to the user’s motion in the space. Therefore, the physical device can simulate a variety of deformable objects by modulating energy parameters during the energy minimization process. Experimental results demonstrate the feasibility of emulating various behaviors of deformable splines, and applying to virtual reality system without interfering with the motion-to-photon latency. We also discuss the method’s limitations and explore its potential. Full article

In this paper, a photosensor-based latency measurement system for head-mounted displays (HMDs) is proposed. The motion-to-photon latency is the greatest reason for motion sickness and dizziness felt by users when wearing an HMD system. Therefore, a measurement system is required to accurately measure and analyze the latency to reduce these problems. The existing measurement system does not consider the actual physical movement in humans, and its accuracy is also very low. However, the proposed system considers the physical head movement and is highly accurate. Specifically, it consists of a head position model-based rotary platform, pixel luminance change detector, and signal analysis and calculation modules. Using these modules, the proposed system can exactly measure the latency, which is the time difference between the physical movement for a user and the luminance change of an output image. In the experiment using a commercial HMD, the latency was measured to be up to 47.05 ms. In addition, the measured latency increased up to 381.17 ms when increasing the rendering workload in the HMD. Full article