Video games are typically executed on Windows platforms with DirectX API and require high performance CPUs and graphics hardware. For pervasive gaming in various environments like at home, hotels, or internet cafes, it is beneficial to run games also on mobile devices and modest performance CE devices avoiding the necessity of placing a noisy workstation in the living room or costly computers/consoles in each room of a hotel. This paper presents a new cross-platform approach for distributed 3D gaming in wired/wireless local networks. We introduce the novel system architecture and protocols used to transfer the game graphics data across the network to end devices. Simultaneous execution of video games on a central server and a novel streaming approach of the 3D graphics output to multiple end devices enable the access of games on low cost set top boxes and handheld devices that natively lack the power of executing a game with high-quality graphical output.
In this work, we present a framework to capture 3D models of faces in high resolutions with low computational load. The system captures only two pictures ofthe face, one illuminated with a colored stripe pattern and one with regular white light. The former is needed for the depth calculation, the latter is used as texture. Having these two images a combination of specialized algorithms is applied to generate a 3D model. The results are shown in different views: simple surface, wire grid respective polygon mesh or textured 3D surface.
In this paper, we present a graphics streaming system for remote gaming in a local area network. The framework aims at creating a networked game platform for home and hotel environments. A local PC based server executes a computer game and streams the graphical output to local devices in the rooms, such that the users can play everywhere in the network. Since delay is extremely crucial in interactive gaming, efficient encoding and caching of the commands is necessary. In our system we also address the round trip time problem of commands requiring feedback from the graphics board by simulating the graphics state at the server. This results in a system that enables interactive game play over the network
In coming years we will see low cost networked consumer electronics (CE) devices dominating the living room. Various applications will be offered, including IPTV, VoIP, VoD, PVR and others. With regards to gaming, the need to compete with PlayStation and Xbox will require a radical change in system architecture. While traditional CE equipment suffers from having to meet low BOM (bill of materials) targets, dictated by highly competitive market and cable companies targeted costs, consoles enjoy superior hardware and software capabilities, being able to offset hardware and BOM costs with software royalties. Exent Technologies is leading the European FP6 Integrated Project Games@Large , whose mission is to research, develop and implement a new platform aimed at providing users with a richer variety of entertainment experience in familiar environments, such as their house, hotel room, and Internet Café. This will support low-cost, ubiquitous gameplay throughout such environments, while taking advantage of existing hardware and providing multiple members of the family and community the ability to play simultaneously and to share experiences. This paper focuses on one of the innovative aspects of the Games@Large project idea -the interactive streaming of graphical output to client devices. This is achieved by capturing the graphical commands at the DirectX API on the server and rendering them locally, resulting in high visual quality and enabling multiple game execution. In order to support also small handheld devices which lack hardware graphics support, an enhanced video method is additionally provided.
We present a system to capture high accuracy 3D models of faces by taking just one photo without the need of specialized hardware, just a consumer grade digital camera and beamer. The proposed 3D face scanner utilizes structured light techniques: A colored pattern is projected into the face of interest while a photo is taken. Then, the 3D geometry is calculated based on the distortions of the pattern detected in the face. This is performed by triangulating the pattern found in the captured image with the projected one
In this paper, augmented reality techniques are used in order to create a virtual mirror for the real-time visualization of customized sports shoes. Similar to looking into a mirror when trying on new shoes in a shop, we create the same impression but for virtual shoes that the customer can design individually. For that purpose, we replace the real mirror by a large display that shows the mirrored input of a camera capturing the legs and shoes of a person. 3-D tracking of both feet and exchanging the real shoes by computer graphics models gives the impression of actually wearing the virtual shoes. The 3-D motion tracker presented in this paper, exploits mainly silhouette information to achieve robust estimates for both shoes from a single camera view. The use of a hierarchical approach in an image pyramid enables real-time estimation at frame rates of more than 30 frames per second
Figure 1: Our approach synthesizes images of clothes from a database of images by interpolating image warps as well as intensities in pose space. AbstractThis paper introduces a new image-based rendering approach for articulated objects with complex pose-dependent appearance, such as clothes. Our approach combines body-pose-dependent appearance and geometry to synthesize images of new poses from a database of examples. A geometric model allows animation and view interpolation, while small details as well as complex shading and reflection properties are modeled by pose-dependent appearance examples in a database. Correspondences between the images are represented as mesh-based warps, both in the spatial and intensity domain. For rendering, these warps are interpolated in pose space, i.e. the space of body poses, using scattered data interpolation methods. Warp estimation as well as geometry reconstruction is performed in an offline procedure, thus shifting computational complexity to an a-priori training phase.
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