No abstract available.

No abstract available.

This work presents FlowZone, an exploratory VR prototype that integrates yoga and mindfulness meditation. The system uses headset and controller data for lightweight pose tracking and provides real-time feedback in guided sessions. A preliminary user study (N=6) revealed common challenges in yoga practice, including uncertainty about pose correctness, difficulty maintaining consistency, and the importance of calming environments. These insights informed the design of FlowZone, which combines accessible pose guidance with immersive, meditation-oriented settings. While not a full evaluation, our early findings suggest that VR yoga and meditation can lower barriers to practice and support stress reduction, pointing toward promising directions for future research.

Climate change education often struggles to connect personal actions with environmental consequences. Meltdown is an immersive VR escape room that teaches sustainable food consumption and waste practices through scenario-based tasks and consequence-driven feedback. A user study (N = 36) found significant gains in familiarity, confidence, and behavioral intentions, with modest knowledge improvements. Exploratory metrics (n = 13) showed high accuracy on familiar decisions but lower accuracy on less intuitive ones. These findings suggest that consequence-driven VR can effectively engage learners, link everyday choices to visible outcomes, and foster sustainable behavior change.

We present VRCare, a VR-based eye screening tool enabling remote, self-guided vision assessments for colour blindness, visual field, myopia, and contrast sensitivity. A user study with 33 participants evaluated usability, comfort, and perceived effectiveness. Participants rated the system highly for intuitiveness (4.45/5), ease of use (4.48/5), and comfort (4.27/5), with 91% willing to reuse the tool. Lower confidence in diagnostic accuracy (3.76/5) and reports of mild discomfort highlight the need for clinical validation and ergonomic refinement. Overall, findings demonstrate VR’s potential for accessible vision screening outside clinical settings.

Abstract Distributed hybrid rendering (DHR) is a real-time rendering approach that incorporates cloud-based ray tracing with locally rasterized graphics for interactive thin client metaverse and game applications. With cloud assistance, DHR can generate high-fidelity ray-traced graphics contents remotely and deliver them to thin clients with low graphics capability, including standalone extended reality devices and mobile phones, while maintaining interactive frame rates for users under adverse network conditions. DHR can already achieve the effect of ray-traced hard shadows that form with the occlusion of direct illumination. We enhance the realism of these shadows by softening their edges with the direction of rays traced and approximating the occlusion of indirect illumination by reconstructing ray-traced ambient occlusion with a modified version of spatiotemporal variance-guided filtering. Our technique uses only 20–30% of the bandwidth of remote rendering and is also tolerant of delays of up to 200 ms with only slight distortion to the shadows along object edges.

With the recent research advancements in generative adversarial networks, synthesizing images from textual descriptions has become an active research area. Their applications in fields such as the use of localizing phrases to identify unseen objects in images is an important part of image understanding and can be useful in many applications that rely on mappings between textual and visual information. Although most zero shot learning algorithms consider the problem to be a visual semantic embedding one, we attempt to utilize the demonstrative capability of Generative Adversarial network [7] for ZSL tasks, similar to [20], where an image is generated based on an object description utilizing a GAN architecture inspired by the cascaded GAN structure used in state of the art text to image frameworks [10], [16], [18], [19] in order to help the network generate more accurate feature vectors that relate to the noisy input text from wikipedia. By using a cascaded structure, we essentially divide the problem into consequent sub-problems that are easier to solve, thus leading to a more positive result on the zero-shot learning task. Our architecture utilizes a cascaded GAN architecture inspired by text-to-image generators like [10], [16], [18], [19] to generate feature vectors that can be applied to the ZSL task at various stages, with each stage increasing the dimension size and complexity of the vector. While the initial stages are responsible for generating low dimension primitive feature vectors, the later stages focus on increasing the complexity of the vector to generate more accurate outputs. The output of each stage is also guided by it's respective discriminator, which tries to classify the vector as real/fake, along with it's corresponding class label. We will empirically compare our model to state of the art of the zero learning models [6], [9], [12], [20] on the CUB and NAB datasets with the SCS and SCE splits introduced in [6], which have been modified by [6] to also include noisy Wikipedia article texts as input for each class. We then compare our architecture with state-of-the-art methods in the Zero-shot-recognition and Generalized Zero-shot learning tasks and present quantitative results for the same.

One in six people have some form of visual impairment ranging from mild vision loss to total blindness. The visually impaired constantly face the danger of walking into people or hazardous objects. This thesis proposes the use of vibrotactile feedback to serve as an obstacle detection system for visually impaired users. We utilize a mixed reality headset with on-board depth sensors to build a digital map of the real world and a suit with an array of actuators to provide feedback as to indicate to the visually impaired the position of obstacles around them. This is demonstrated by a simple prototype built using commercially available devices (Microsoft HoloLens and bHaptics Tactot) and a qualitative user study was conducted to evaluate the viability of the proposed system. Through our user-testing performed on subjects with simulated visual impairments, our results affirm the potential of using mixed reality to detect obstacles in the environment along with only transmitting essential information through the haptic suit due to limited bandwidth.

Interest in fine-grained indoor localization remains high and various approaches including those based on Radio Frequency (RF), ultrasound, acoustic, magnetic field and light have been proposed. However, while the achieved accuracy may be high, many of these approaches do not work well in environments with lots of obstructions. In this paper, we present MagB, a decimeter-level localization scheme that uses the magnetometer available on many IoT devices. MagB estimates the bearing of magnetic beacons by detecting changes in the magnetic field strength. Localization is then performed based on Angle-of-Arrival (AoA) information. We have built a prototype of MagB using low cost, off-the-shelf components. Our evaluation shows that MagB is able to achieve a median accuracy of about 13cm and can localize devices even when they are placed in steel filing cabinet or inside the casing of a running PC.

Beacons, the backbone of the physical web and location-based services, are widely used to tag objects and places. However, as a beacon's wireless transmission is limited to a ranging technology, the localization information is only available when the beacon is nearby.

Emerged as a choice of display for vivid colours and power efficiency in expensive Smartphones, in recent days Organic Light Emitting Diode (OLED) displays are increasingly replacing Liquid Crystal Displays (LCD) and Plasma in Smartphones and large screen Televisions. Yet, OLED displays are one of the most energy consuming modules in modern Smartphones. Power consumption of OLED displays have strong correlation with the colours illuminated by its pixels. Improvements in pixel density by manufacturers makes the displays more power hungry. In this paper, we present Human Visual System (HVS) aware adaptive colour transformation and darkening methods to create power-efficient videos for OLED displays while preserving visual fidelity of the videos. Our measurements and subjective evaluations show that we can save up to 60% of energy consumption with minimum distortion to visual quality of the video. As our colour transformation process uses pre-computed colour-map and the darkening process uses the gamma-correction function which is already implemented in most of the display hardware, runtime computation overheads are minimum and hence, our method can be used to manipulate realtime/live video streams as well.

This technical demonstration presents the SuperStreamer project, which enables progressive game assets streaming to players while games are played, reducing the startup time required to download and start playing a cloud-based game. SuperStreamer modifies a popular game engine, Unreal Engine 4, to support developing and playing games with progressive game asset streaming. With SuperStreamer, developers can mark the minimal set of files, containing only the game content essential to start playing the game. When a player plays the game, these minimal set of files will be downloaded to the player's device. SuperStreamer also generates low resolution textures automatically when a developer publishes a game, and these low resolution textures are transmitted first into the game client. As players move through a game level, high quality textures required for the game will be downloaded. In our demo game, we are able to decrease the time taken to startup and load the first game level by around 30%.

The use of recording applications for teaching is increasingly popular, with tools such as Ink2Go and ShowMe being available on many platforms and at reasonable cost. However, most recording applications available are typically native applications and do not work within the web browser. In this work, we study the feasibility of implementing a recording solution in the web browser environment.

As the current generation of mobile smartphones become more powerful, they are being used to perform more resource intensive tasks making battery lifetime a major bottle-neck. In this paper, we present a technique called dynamic AoV lookahead for reducing wireless interface power consumption upto 50% while playing a popular, yet resource intensive, mobile multiplayer games.

Due to their thin size, vivid colors, high contrast and power efficiency, OLED (Organic Light-Emitting Diode) display and its variants such as AMOLED (Active Matrix OLED) displays are increasingly replacing traditional LCD (Liquid Crystal Display) screens in smart phones. However, the power efficiency of OLED screens greatly depends on the luminance and colors of the displayed contents on the screen. Web browsing is one of the most widely used applications in mobile devices. In this paper, we present our cloud service, which intelligently re-paints the web pages in real-time with power efficient colors and HVS (Human Visual System) based tone mapping techniques, without adversely affecting the identity (brand color) of the web pages as well as the user's browsing experience. El-pincel helps to save up to 60% of OLED energy with color combinations that ensure good legibility and pleasing affective response to human eyes.

Due to their thin size, vivid colors, high contrast and power efficiency, OLED and its variants such as AMOLED screens are increasingly replacing traditional LCD screens in mobile phones (eg. Google Nexus One, Samsung Galaxy S phones). However, the power efficiency of OLED screens greatly depends on the luminance and colors of the displayed contents on the screen. Web browsing is one of the most widely used applications in mobile devices. We demonstrate our cloud service, which intelligently re-paints the web pages in real-time with power efficient colors and tone mapping techniques without adversely affecting the user experience in reading the page and the identity of the page. Transformation of images, flash contents and videos in client itself will incur significant computational and energy overhead. El-pincel is designed as a cloud service to avoid any additional overhead to the mobile device.

In this paper, we show how tone mapping techniques can be used to dynamically increase the image brightness, thus allowing the LCD backlight levels to be reduced. This saves significant power as the majority of the LCD's display power is consumed by its backlight. The Gamma function (or equivalent) can be efficiently implemented in smartphones with minimal resource cost. We describe how we overcame the Gamma function's non-linear nature by using adaptive thresholds to apply different Gamma values to images with differing brightness levels. These adaptive thresholds allow us to save significant amounts of power while preserving the image quality. We implemented our solution on a laptop and two Android smartphones. Finally, we present measured analytical results for two different games (Quake III and Planeshift), and user study results (using Quake III and 60 participants) that shows that we can save up to 68% of the display power without significantly affecting the perceived gameplay quality.

The current generation of mobile smartphones are not just devices for voice communication. Instead, they are frequently used as mobile PC replacements that are used to edit documents, browse the web, check email, and play games. However, this functionality comes at the cost of battery lifetimes. Indeed, to maintain the slim form factor required for these phones (which impacts the amount of battery that can be put into the phone), it is quite common for the battery lifetimes of smartphones to be significantly shorter compared to previous generation of "dumber" phones.