38 results
Search Results
Now showing 1 - 10 of 38
Item ManyLoDs: Parallel Many-View Level-of-Detail Selection for Real-Time Global Illumination(The Eurographics Association and Blackwell Publishing Ltd., 2011) Holländer, Matthias; Ritschel, Tobias; Eisemann, Elmar; Boubekeur, Tamy; Ravi Ramamoorthi and Erik ReinhardLevel-of-Detail structures are a key component for scalable rendering. Built from raw 3D data, these structures are often defined as Bounding Volume Hierarchies, providing coarse-to-fine adaptive approximations that are well-adapted for many-view rasterization. Here, the total number of pixels in each view is usually low, while the cost of choosing the appropriate LoD for each view is high. This task represents a challenge for existing GPU algorithms. We propose ManyLoDs, a new GPU algorithm to efficiently compute many LoDs from a Bounding Volume Hierarchy in parallel by balancing the workload within and among LoDs. Our approach is not specific to a particular rendering technique, can be used on lazy representations such as polygon soups, and can handle dynamic scenes. We apply our method to various many-view rasterization applications, including Instant Radiosity, Point-Based Global Illumination, and reflection / refraction mapping. For each of these, we achieve real-time performance in complex scenes at high resolutions.Item Geometry and Attribute Compression for Voxel Scenes(The Eurographics Association and John Wiley & Sons Ltd., 2016) Dado, Bas; Kol, Timothy R.; Bauszat, Pablo; Thiery, Jean-Marc; Eisemann, Elmar; Joaquim Jorge and Ming LinVoxel-based approaches are today's standard to encode volume data. Recently, directed acyclic graphs (DAGs) were successfully used for compressing sparse voxel scenes as well, but they are restricted to a single bit of (geometry) information per voxel. We present a method to compress arbitrary data, such as colors, normals, or reflectance information. By decoupling geometry and voxel data via a novel mapping scheme, we are able to apply the DAG principle to encode the topology, while using a palette-based compression for the voxel attributes, leading to a drastic memory reduction. Our method outperforms existing state-of-the-art techniques and is well-suited for GPU architectures. We achieve real-time performance on commodity hardware for colored scenes with up to 17 hierarchical levels (a 128K3 voxel resolution), which are stored fully in core.Item Compressed Multiresolution Hierarchies for High-Quality Precomputed Shadows(The Eurographics Association and John Wiley & Sons Ltd., 2016) Scandolo, Leonardo; Bauszat, Pablo; Eisemann, Elmar; Joaquim Jorge and Ming LinThe quality of shadow mapping is traditionally limited by texture resolution. We present a novel lossless compression scheme for high-resolution shadow maps based on precomputed multiresolution hierarchies. Traditional multiresolution trees can compactly represent homogeneous regions of shadow maps at coarser levels, but require many nodes for fine details. By conservatively adapting the depth map, we can significantly reduce the tree complexity. Our proposed method offers high compression rates, avoids quantization errors, exploits coherency along all data dimensions, and is well-suited for GPU architectures. Our approach can be applied for coherent shadow maps as well, enabling several applications, including high-quality soft shadows and dynamic lights moving on fixed-trajectories.Item An Interactive Information Visualization Approach to Physically-Based Rendering(The Eurographics Association, 2016) Simons, Gerard; Ament, Marco; Herholz, Sebastian; Dachsbacher, Carsten; Eisemann, Martin; Eisemann, Elmar; Matthias Hullin and Marc Stamminger and Tino WeinkaufIn this work, we present a novel information visualization tool to gain insight into the light transport in a physically-based rendering setting. The tool consists of a sampling-based data reduction technique, an extended interactive parallel coordinates plot providing an overview of the attributes linked to each light sample, 2D and 3D heat maps to represent different aspects of the rendering process, as well as a three-dimensional view to display and animate the light path transportation throughout the scene. We show several applications including differential light transport visualization for scene analysis, lighting and material optimization, reduction of rendering artifacts, and user-guided importance sampling.Item Interactive Indirect Illumination Using Voxel Cone Tracing(The Eurographics Association and Blackwell Publishing Ltd., 2011) Crassin, Cyril; Neyret, Fabrice; Sainz, Miguel; Green, Simon; Eisemann, Elmar; Bing-Yu Chen, Jan Kautz, Tong-Yee Lee, and Ming C. LinIndirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the involved surfaces. While off-line computation and pre-baking can be acceptable for some cases, many applications (games, simulators, etc.) require real-time or interactive approaches to evaluate indirect illumination. We present a novel algorithm to compute indirect lighting in real-time that avoids costly precomputation steps and is not restricted to low-frequency illumination. It is based on a hierarchical voxel octree representation generated and updated on the fly from a regular scene mesh coupled with an approximate voxel cone tracing that allows for a fast estimation of the visibility and incoming energy. Our approach can manage two light bounces for both Lambertian and glossy materials at interactive framerates (25-70FPS). It exhibits an almost scene-independent performance and can handle complex scenes with dynamic content thanks to an interactive octree-voxelization scheme. In addition, we demonstrate that our voxel cone tracing can be used to efficiently estimate Ambient Occlusion.Item Merged Multiresolution Hierarchies for Shadow Map Compression(The Eurographics Association and John Wiley & Sons Ltd., 2016) Scandolo, Leonardo; Bauszat, Pablo; Eisemann, Elmar; Eitan Grinspun and Bernd Bickel and Yoshinori DobashiMultiresolution Hierarchies (MH) and Directed Acyclic Graphs (DAG) are two recent approaches for the compression of highresolution shadow information. In this paper, we introduce Merged Multiresolution Hierarchies (MMH), a novel data structure that unifies both concepts. An MMH leverages both hierarchical homogeneity exploited in MHs, as well as topological similarities exploited in DAG representations. We propose an efficient hash-based technique to quickly identify and remove redundant subtree instances in a modified relative MH representation. Our solution remains lossless and significantly improves the compression rate compared to both preceding shadow map compression algorithms, while retaining the full run-time performance of traditional MH representations.Item Hierarchical Stochastic Neighbor Embedding(The Eurographics Association and John Wiley & Sons Ltd., 2016) Pezzotti, Nicola; Höllt, Thomas; Lelieveldt, Boudewijn P. F.; Eisemann, Elmar; Vilanova, Anna; Kwan-Liu Ma and Giuseppe Santucci and Jarke van WijkIn recent years, dimensionality-reduction techniques have been developed and are widely used for hypothesis generation in Exploratory Data Analysis. However, these techniques are confronted with overcoming the trade-off between computation time and the quality of the provided dimensionality reduction. In this work, we address this limitation, by introducing Hierarchical Stochastic Neighbor Embedding (Hierarchical-SNE). Using a hierarchical representation of the data, we incorporate the wellknown mantra of Overview-First, Details-On-Demand in non-linear dimensionality reduction. First, the analysis shows an embedding, that reveals only the dominant structures in the data (Overview). Then, by selecting structures that are visible in the overview, the user can filter the data and drill down in the hierarchy. While the user descends into the hierarchy, detailed visualizations of the high-dimensional structures will lead to new insights. In this paper, we explain how Hierarchical-SNE scales to the analysis of big datasets. In addition, we show its application potential in the visualization of Deep-Learning architectures and the analysis of hyperspectral images.Item VarVis: Visualizing Anatomical Variation in Branching Structures(The Eurographics Association, 2016) Smit, Noeska; Kraima, Annelot; Jansma, Daniel; deRuiter, Marco; Eisemann, Elmar; Vilanova, Anna; Enrico Bertini and Niklas Elmqvist and Thomas WischgollAnatomical variations are naturally-occurring deviations from typical human anatomy. While these variations are considered normal and non-pathological, they are still of interest in clinical practice for medical specialists such as radiologists and transplantation surgeons. The complex variations in branching structures, for instance in arteries or nerves, are currently visualized side-by-side in illustrations or expressed using plain text in medical publications. In this work, we present a novel way of visualizing anatomical variations in complex branching structures for educational purposes: VarVis. VarVis consists of several linked views that reveal global and local similarities and differences in the variations. We propose a novel graph representation to provide an overview of the topological changes. Our solution involves a topological similarity measure, which allows the user to select variations at a global level based on their degree of similarity. After a selection is made, local topological differences can be interactively explored using illustrations and topology graphs. We also incorporate additional information regarding the probability of the various cases. Our solution has several advantages over traditional approaches, which we demonstrate in an evaluation.Item Mapping Images to Target Devices: Spatial, Temporal, Stereo, Tone, and Color(The Eurographics Association, 2012) Banterle, Francesco; Artusi, Alessandro; Aydin, Tunc O.; Didyk, Piotr; Eisemann, Elmar; Gutierrez, Diego; Mantiuk, Rafael; Myszkowski, Karol; Ritschel, Tobias; Renato Pajarola and Michela SpagnuoloRetargeting is a process through which an image or a video is adapted from the display device for which it was meant (target display) to another one (retarget display). The retarget display can have different features from the target one such as: dynamic range, discretization levels, color gamut, multi-view (3D), refresh rate, spatial resolution, etc. This tutorial presents the latest solutions and techniques for retargeting images along various dimensions (such as dynamic range, colors, temporal and spatial resolutions) and offers for the first time a much-needed holistic view of the field. This includes how to measure and analyze the changes applied to an image/video in terms of quality using both (subjective) psychophysical experiments and (objective) computational metrics.Item Real-time Canonical-angle Views in 3D Virtual Cities(The Eurographics Association, 2014) Kol, Timothy R.; Liao, Jingtang; Eisemann, Elmar; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp UrbanVirtual city models are useful for navigation planning or the investigation of unknown regions. However, existing rendering systems often fail to provide optimal views during the exploration, introduce occlusions, or show the buildings from the top only, which limits the amount of useful visual information accessible to the user. In consequence, users are forced to interact more extensively with the application to avoid these shortcomings. This process can be quite time-consuming. In this paper, we propose a new technique based on canonical views to address these problems. We compute every building's canonical view and, dynamically, transform it correspondingly, so that it is easy to identify under all camera angles. A user study was conducted to assess how this technique compares to a regular view; our method improves the recognizability of the buildings and helps the users explore the virtual city more efficiently. The results indicate that using canonical views is beneficial for efficient navigation in virtual cities.