Durability of Wireless Charging Systems Embedded Into Concrete Pavements for Electric Vehicles

Point clouds are widely used in various applications such as 3D modeling, geospatial analysis, robotics, and more. One of the key advantages of 3D point cloud data is that, unlike other data formats like texture, it is independent of viewing angle, surface type, and parameterization. Since each point in the point cloud is independent of the other, it makes it the most suitable source of data for tasks like object recognition, scene segmentation, and reconstruction. Point clouds are complex and verbose due to the numerous attributes they contain, many of which may not be always necessary for rendering, making retrieving and parsing a heavy task. As Sensors are becoming more precise and popular, effectively streaming, processing, and rendering the data is also becoming more challenging. In a hierarchical continuous LOD system, the previously fetched and rendered data for a region may become unavailable when revisiting it. To address this, we use a non-persistence cache using hash-map which stores the parsed point attributes, which still has some limitations, such as the dataset needing to be refetched and reprocessed if the tab or browser is closed and reopened which can be addressed by persistence caching. On the web, popularly persistence caching involves storing data in server memory, or an intermediate caching server like Redis. This is not suitable for point cloud data where we have to store parsed and processed large point data making point cloud visualization rely only on non-persistence caching. The thesis aims to contribute toward better performance and suitability of point cloud rendering on the web reducing the number of read requests to the remote file to access data.We achieve this with the application of client-side-based LRU Cache and Private File Open Space as a combination of both persistence and non-persistence caching of data. We use a cloud-optimized data format, which is better suited for web and streaming hierarchical data structures. Our focus is to improve rendering performance using WebGPU by reducing access time and minimizing the amount of data loaded in GPU. Preliminary results indicate that our approach significantly improves rendering performance and reduce network request when compared to traditional caching methods using WebGPU

LiveVV: Human-Centered Live Volumetric Video Streaming System

Volumetric video has emerged as a prominent medium within the realm of eXtended Reality (XR) with the advancements in computer graphics and depth capture hardware. Users can fully immersive themselves in volumetric video with the ability to switch their viewport in six degree-of-freedom (DOF), including three rotational dimensions (yaw, pitch, roll) and three translational dimensions (X, Y, Z). Different from traditional 2D videos that are composed of pixel matrices, volumetric videos employ point clouds, meshes, or voxels to represent a volumetric scene, resulting in significantly larger data sizes. While previous works have successfully achieved volumetric video streaming in video-on-demand scenarios, the live streaming of volumetric video remains an unresolved challenge due to the limited network bandwidth and stringent latency constraints. In this paper, we for the first time propose a holistic live volumetric video streaming system, LiveVV, which achieves multi-view capture, scene segmentation \& reuse, adaptive transmission, and rendering. LiveVV contains multiple lightweight volumetric video capture modules that are capable of being deployed without prior preparation. To reduce bandwidth consumption, LiveVV processes static and dynamic volumetric content separately by reusing static data with low disparity and decimating data with low visual saliency. Besides, to deal with network fluctuation, LiveVV integrates a volumetric video adaptive bitrate streaming algorithm (VABR) to enable fluent playback with the maximum quality of experience. Extensive real-world experiment shows that LiveVV can achieve live volumetric video streaming at a frame rate of 24 fps with a latency of less than 350ms

3DRepo4Unity: Dynamic Loading of Version Controlled 3D Assets into the Unity Game Engine

In recent years, Unity has become a popular platform for the development of a broad range of visualization and VR applications. This is due to its ease of use, cross-platform compatibility and accessibility to independent developers. Despite such applications being cross-platform, their assets are generally bundled with executables, or streamed at runtime in a highly optimised, proprietary format. In this paper, we present a novel system for dynamically populating a Unity environment at runtime using open Web3D standards. Our system generates dynamic resources at runtime from a remote 3D Repo repository. This enables us to build a viewer which can easily visualize X3D-based revisions from a version controlled database in the cloud without any compile-time knowledge of the assets. We motivate the work and introduce the high-level architecture of our solution. We describe our new dynamic transcoding library with an emphasis on scalability and 3D rendering. We then perform a comparative evaluation between 3drepo.io, a state of the art X3DOM based renderer, and the new 3DRepo4Unity library on web browser platforms. Finally, we present a number of different applications that demonstrate the practicality of our chosen approach. By building on previous Web3D functionality and standards, our hope is to stimulate further discussion around and research into web formats that would enable incremental loading on other platforms

Service oriented interactive media (SOIM) engines enabled by optimized resource sharing

In the same way as cloud computing, Software as a Service (SaaS) and Content Centric Networking (CCN) triggered a new class of software architectures fundamentally different from traditional desktop software, service oriented networking (SON) suggests a new class of media engine technologies, which we call Service Oriented Interactive Media (SOIM) engines. This includes a new approach for game engines and more generally interactive media engines for entertainment, training, educational and dashboard applications. Porting traditional game engines and interactive media engines to the cloud without fundamentally changing the architecture, as done frequently, can enable already various advantages of cloud computing for such kinds of applications, for example simple and transparent upgrading of content and unified user experience on all end-user devices. This paper discusses a new architecture for game engines and interactive media engines fundamentally designed for cloud and SON. Main advantages of SOIM engines are significantly higher resource efficiency, leading to a fraction of cloud hosting costs. SOIM engines achieve these benefits by multilayered data sharing, efficiently handling many input and output channels for video, audio, and 3D world synchronization, and smart user session and session slot management. Architecture and results of a prototype implementation of a SOIM engine are discussed

Mobile graphics: SIGGRAPH Asia 2017 course

Peer ReviewedPostprint (published version

From capturing to rendering : volumetric media delivery with six degrees of freedom

Technological improvements are rapidly advancing holographic-type content distribution. Significant research efforts have been made to meet the low latency and high bandwidth requirements set forward by interactive applications such as remote surgery and virtual reality. Recent research made six degrees of freedom (6DoF) for immersive media possible, where users may both move their head and change their position within a scene. In this article, we present the status and challenges of 6DoF applications based on volumetric media, focusing on the key aspects required to deliver such services. Furthermore, we present results from a subjective study to highlight relevant directions for future research