The Moving Picture Company (a) Cloud -100 steps -8 fps (b) TinPan Alley -500 steps -10 fps (c) GI-Joe * -50 steps -3000 lights -7minFigure 1: Our algorithm introduces transmittance function maps for the computation of light scattering within participating media for both real-time using a GeForce GTX480 (a, b) and production rendering (c) using Pixar's RenderMan R . AbstractThe interaction between light and participating media involves complex physical phenomena including light absorption and scattering. Media such as fog, clouds or smoke feature complex lighting interactions that are intrinsically related to the properties of their constitutive particles. As a result, the radiance transmitted by the medium depends on the varying properties on the entire light paths, which generate soft light shafts and opacity variations.Simulating light scattering in these media usually requires complex offline estimations. Real-time applications are either based on heavy precomputations, limited to homogeneous media or relying on simplistic rendering techniques such as billboards. We propose a generic method for fast estimation of single scattering within participating media. Introducing the concept of Transmittance Function Maps and Uniform Projective Space Sampling, our method leverages graphics hardware for interactive support of dynamic light sources, viewpoints and participating media. Our method also accounts for the shadows cast from solid objects, providing a fullfeatured solution for fast rendering of participating media which potentially embrace the entire scene.

Background. When the physiological activity of the brain (e.g., electroencephalogram, functional magnetic resonance imaging, etc.) is monitored in real-time, feedback can be returned to the subject and he/she can try to exercise some control over it. This idea is at the base of research on neurofeedback and brain-computer interfaces. Current advances in the speed of microprocessors, graphics cards and digital signal processing algorithms allow significant improvements in these methods. More meaningful features from the continuous flow of brain activation can be extracted and feedback can be more informative.Methods. Borrowing technology so far employed only in virtual reality, we have created Open-ViBE (Open Platform for Virtual Brain Environments). Open-ViBE is a general purpose platform for the development of three dimensional real-time virtual representations of brain physiological and anatomical data. Open-ViBE is a flexible and modular platform that integrates modules for brain physiological data acquisition, processing, and volumetric rendering.Results. When input data is the electroencephalogram, Open-ViBE uses the estimation of intra-cranial current density to represent brain activation as a regular grid of three dimensional graphical objects. The color and size of these objects co-vary with the amplitude and/or direction of the electrical current. This representation can be superimposed onto a volumetric rendering of the subject's MRI data to form the anatomical background of the scene. The user can navigate in this virtual brain and visualize it as a whole or only some of its parts. This allows the user to experience the sense of presence (being there) in the scene and to observe the dynamics of brain current activity in its original spatio-temporal relations.Conclusions. The platform is based on publicly available frameworks such as OpenMASK and OpenSG and is open source itself. In this way we aim to enhance the cooperation of researchers and to promote the use of the platform on a large scale.

Figure 1: Production pipeline of stroke-based buildings. The edges of facade images are extracted and vectorized. This vector data is used instead of textures to represent the facade in the final 3D model. AbstractIn this paper, we present a new approach for remote visualization of large 3D cities. Our approach is based on expressive rendering (also known as Non-Photorealistic Rendering), and more precisely, on feature lines. By focusing on characteristic features, this solution brings a more legible visualization and reduces the amount of data transmitted on the network. We also introduce a client-server system for remote rendering, as well as the involved pre-processing stage that is required for optimization. Based on the presented system, we perform a study on the usability of such an approach in the context of mobile devices.

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