Doctor of Philosophy

dissertationRay tracing presents an efficient rendering algorithm for scientific visualization using common visualization tools and scales with increasingly large geometry counts while allowing for accurate physically-based visualization and analysis, which enables enhanced rendering and new visualization techniques. Interactivity is of great importance for data exploration and analysis in order to gain insight into large-scale data. Increasingly large data sizes are pushing the limits of brute-force rasterization algorithms present in the most widely-used visualization software. Interactive ray tracing presents an alternative rendering solution which scales well on multicore shared memory machines and multinode distributed systems while scaling with increasing geometry counts through logarithmic acceleration structure traversals. Ray tracing within existing tools also provides enhanced rendering options over current implementations, giving users additional insight from better depth cues while also enabling publication-quality rendering and new models of visualization such as replicating photographic visualization techniques

Scalable Real-Time Rendering for Extremely Complex 3D Environments Using Multiple GPUs

In 3D visualization, real-time rendering of high-quality meshes in complex 3D environments is still one of the major challenges in computer graphics. New data acquisition techniques like 3D modeling and scanning have drastically increased the requirement for more complex models and the demand for higher display resolutions in recent years. Most of the existing acceleration techniques using a single GPU for rendering suffer from the limited GPU memory budget, the time-consuming sequential executions, and the finite display resolution. Recently, people have started building commodity workstations with multiple GPUs and multiple displays. As a result, more GPU memory is available across a distributed cluster of GPUs, more computational power is provided throughout the combination of multiple GPUs, and a higher display resolution can be achieved by connecting each GPU to a display monitor (resulting in a tiled large display configuration). However, using a multi-GPU workstation may not always give the desired rendering performance due to the imbalanced rendering workloads among GPUs and overheads caused by inter-GPU communication. In this dissertation, I contribute a multi-GPU multi-display parallel rendering approach for complex 3D environments. The approach has the capability to support a high-performance and high-quality rendering of static and dynamic 3D environments. A novel parallel load balancing algorithm is developed based on a screen partitioning strategy to dynamically balance the number of vertices and triangles rendered by each GPU. The overhead of inter-GPU communication is minimized by transferring only a small amount of image pixels rather than chunks of 3D primitives with a novel frame exchanging algorithm. The state-of-the-art parallel mesh simplification and GPU out-of-core techniques are integrated into the multi-GPU multi-display system to accelerate the rendering process

Time and Space Coherent Occlusion Culling for Tileable Extended 3D Worlds

International audienceIn order to interactively render large virtual worlds, the amount of 3D geometry passed to the graphics hardware must be kept to a minimum. Typical solutions to this problem include the use of potentially visible sets and occlusion culling, however, these solutions do not scale well, in time nor in memory, with the size of a virtual world. We propose a fast and inexpensive variant of occlusion culling tailored to a simple tiling scheme that improves scalability while maintaining very high performance. Tile visibilities are evaluated with hardwareaccelerated occlusion queries, and in-tile rendering is rapidly computed using BVH instantiation and any visibility method; we use the CHC++ occlusion culling method for its good general performance. Tiles are instantiated only when tested locally for visibility, thus avoiding the need for a preconstructed global structure for the complete world. Our approach can render large-scale, diversified virtual worlds with complex geometry, such as cities or forests, all at high performance and with a modest memory footprint

Point based graphics rendering with unified scalability solutions.

Standard real-time 3D graphics rendering algorithms use brute force polygon rendering, with complexity linear in the number of polygons and little regard for limiting processing to data that contributes to the image. Modern hardware can now render smaller scenes to pixel levels of detail, relaxing surface connectivity requirements. Sub-linear scalability optimizations are typically self-contained, requiring specific data structures, without shared functions and data. A new point based rendering algorithm 'Canopy' is investigated that combines multiple typically sub-linear scalability solutions, using a small core of data structures. Specifically, locale management, hierarchical view volume culling, backface culling, occlusion culling, level of detail and depth ordering are addressed. To demonstrate versatility further, shadows and collision detection are examined. Polygon models are voxelized with interpolated attributes to provide points. A scene tree is constructed, based on a BSP tree of points, with compressed attributes. The scene tree is embedded in a compressed, partitioned, procedurally based scene graph architecture that mimics conventional systems with groups, instancing, inlines and basic read on demand rendering from backing store. Hierarchical scene tree refinement constructs an image tree image space equivalent, with object space scene node points projected, forming image node equivalents. An image graph of image nodes is maintained, describing image and object space occlusion relationships, hierarchically refined with front to back ordering to a specified threshold whilst occlusion culling with occluder fusion. Visible nodes at medium levels of detail are refined further to rasterization scales. Occlusion culling defines a set of visible nodes that can support caching for temporal coherence. Occlusion culling is approximate, possibly not suiting critical applications. Qualities and performance are tested against standard rendering. Although the algorithm has a 0(f) upper bound in the scene sizef, it is shown to practically scale sub-linearly. Scenes with several hundred billion polygons conventionally, are rendered at interactive frame rates with minimal graphics hardware support

Visualization of urban environments

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2007.Thesis (Ph. D.) -- Bilkent University, 2007.Includes bibliographical references leaves 108-118Modeling and visualization of large geometric environments is a popular research area in computer graphics. In this dissertation, a framework for modeling and stereoscopic visualization of large and complex urban environments is presented. The occlusion culling and view-frustum culling is performed to eliminate most of the geometry that do not contribute to the user’s final view. For the occlusion culling process, the shrinking method is employed but performed using a novel Minkowski-difference-based approach. In order to represent partial visibility, a novel building representation method, called the slice-wise representation is developed. This method is able to represent the preprocessed partial visibility with huge reductions in the storage requirement. The resultant visibility list is rendered using a graphics-processing-unit-based algorithm, which perfectly fits into the proposed slice-wise representation. The stereoscopic visualization depends on the calculated eye positions during walkthrough and the visibility lists for both eyes are determined using the preprocessed occlusion information. The view-frustum culling operation is performed once instead of two for both eyes. The proposed algorithms were implemented on personal computers. Performance experiments show that, the proposed occlusion culling method and the usage of the slice-wise representation increase the frame rate performance by 81 %; the graphics-processing-unit-based display algorithm increases it by an additional 315 % and decrease the storage requirement by 97 % as compared to occlusion culling using building-level granularity and not using the graphics hardware. We show that, a smooth and real-time visualization of large and complex urban environments can be achieved by using the proposed framework.Yılmaz, TürkerPh.D

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

Scalable Realtime Rendering and Interaction with Digital Surface Models of Landscapes and Cities

Interactive, realistic rendering of landscapes and cities differs substantially from classical terrain rendering. Due to the sheer size and detail of the data which need to be processed, realtime rendering (i.e. more than 25 images per second) is only feasible with level of detail (LOD) models. Even the design and implementation of efficient, automatic LOD generation is ambitious for such out-of-core datasets considering the large number of scales that are covered in a single view and the necessity to maintain screen-space accuracy for realistic representation. Moreover, users want to interact with the model based on semantic information which needs to be linked to the LOD model. In this thesis I present LOD schemes for the efficient rendering of 2.5d digital surface models (DSMs) and 3d point-clouds, a method for the automatic derivation of city models from raw DSMs, and an approach allowing semantic interaction with complex LOD models. The hierarchical LOD model for digital surface models is based on a quadtree of precomputed, simplified triangle mesh approximations. The rendering of the proposed model is proved to allow real-time rendering of very large and complex models with pixel-accurate details. Moreover, the necessary preprocessing is scalable and fast. For 3d point clouds, I introduce an LOD scheme based on an octree of hybrid plane-polygon representations. For each LOD, the algorithm detects planar regions in an adequately subsampled point cloud and models them as textured rectangles. The rendering of the resulting hybrid model is an order of magnitude faster than comparable point-based LOD schemes. To automatically derive a city model from a DSM, I propose a constrained mesh simplification. Apart from the geometric distance between simplified and original model, it evaluates constraints based on detected planar structures and their mutual topological relations. The resulting models are much less complex than the original DSM but still represent the characteristic building structures faithfully. Finally, I present a method to combine semantic information with complex geometric models. My approach links the semantic entities to the geometric entities on-the-fly via coarser proxy geometries which carry the semantic information. Thus, semantic information can be layered on top of complex LOD models without an explicit attribution step. All findings are supported by experimental results which demonstrate the practical applicability and efficiency of the methods