Occlusion Culling Research Articles

Multi-scale data visualization for computational astrophysics and climate dynamics at Oak Ridge National Laboratory

Computational astrophysics and climate dynamics are two principal application foci at the Center for Computational Sciences (CCS) at Oak Ridge National Laboratory (ORNL). We identify a dataset frontier that is shared by several SciDAC computational science domains and present an exploration of traditional production visualization techniques enhanced with new enabling research technologies such as advanced parallel occlusion culling and high resolution small multiples statistical analysis. In collaboration with our research partners, these techniques will allow the visual exploration of a new generation of peta-scale datasets that cross this data frontier along all axes.

Interactive visualization of complex dynamic virtual environments for industrial assemblies

Interactive visualization of assemblies in a virtual environment is important to the industrial applications like design verification and maintenance processes training. In general, the difficulty and the complication of the interactive visualization of industrial assemblies arise from the facts that an assembly model generally has a large number of primitives and high depth complexity; furthermore, dynamic environments are required for simulating assembly manipulations. In this paper, a dynamic data model for visualization of industrial assemblies is proposed. The data model integrates a spatial data set of hierarchical model representation and a dynamic transformation mechanism for runtime adaptation to the changes and movements of the assembly structures. Based on the dynamic spatial database, a visibility optimization approach that can efficiently reduce the overall geometry is presented. The complexity reduction is accomplished through view frustum culling, non-conservative occlusion culling, and geometry simplification. By which, significant speedup in user interaction rates has been achieved. Since all the techniques developed here are supported by mainstream graphics hardware, thus the solution is able to provide users with practical real-time visualization of complex dynamic virtual assembly environments with affordable graphics hardware.

Modeling Very Complex Geometric Assemblies: The Use of Discrete and Hierarchical Models

AbstractVirtual Reality (VR) Systems allow immersive inspection of very complex environments, with direct interaction with the objects in the virtual scene. Low cost and affordable VR systems are becoming essential in application areas like Industrial Design, Medical Applications and Cultural Heritage and require sophisticated techniques for model inspection and interaction. Discrete geometric models can be very useful for some involved geometry processing algorithms like model repair, occlusion culling and multi-resolution and level of detail. The interest of these techniques and their potential in present and future VR applications will be discussed. This paper addresses the interest of discrete geometric models in volume-based geometric simplification, the use of discrete tiles for impostorbased extreme simplification, topology preserving model repair techniques based on discrete membranes and specific algorithms for recovering polygonal shapes from discrete volume models. The use of out-of-core octree...

Generation of Dynamic Infrared Outer Space Scene

This paper proposes a new method to generate the dynamic infrared outer space scene in real time. In the paper, we first model the dynamic infrared background of star sky based on the infrared star catalogue and temporal and spacial coordinate transformations. We also present a new concept called infrared star magnitude for given infrared receiving wavebands to display the infrared star sky effectively. Then we put forward an infrared image synthesis model for outer space targets based on the method of divided elements and energy equilibrium. To generate the dynamic infrared outer space scene, several simplification and accelerating techniques such as Billboard, Levels of Details and Occlusion Culling are hired to accelerate the generating speed of the scene. Finally infrared images of targets, background of outer space scene at different infrared receiving wavebands are drawn and the dynamic infrared outer space scene is successfully carried out in real time.

Quick-VDR: Out-of-Core View-Dependent Rendering of Gigantic Models

We present a novel approach for interactive view-dependent rendering of massive models. Our algorithm combines view-dependent simplification, occlusion culling, and out-of-core rendering. We represent the model as a clustered hierarchy of progressive meshes (CHPM). We use the cluster hierarchy for coarse-grained selective refinement and progressive meshes for fine-grained local refinement. We present an out-of-core algorithm for computation of a CHPM that includes cluster decomposition, hierarchy generation, and simplification. We introduce novel cluster dependencies in the preprocess to generate crack-free, drastic simplifications at runtime. The clusters are used for LOD selection, occlusion culling, and out-of-core rendering. We add a frame of latency to the rendering pipeline to fetch newly visible clusters from the disk and avoid stalls. The CHPM reduces the refinement cost of view-dependent rendering by more than an order of magnitude as compared to a vertex hierarchy. We have implemented our algorithm on a desktop PC. We can render massive CAD, isosurface, and scanned models, consisting of tens or a few hundred million triangles at 15-35 frames per second with little loss in image quality.

Far voxels

We present an efficient approach for end-to-end out-of-core construction and interactive inspection of very large arbitrary surface models. The method tightly integrates visibility culling and out-of-core data management with a level-of-detail framework. At preprocessing time, we generate a coarse volume hierarchy by binary space partitioning the input triangle soup. Leaf nodes partition the original data into chunks of a fixed maximum number of triangles, while inner nodes are discretized into a fixed number of cubical voxels. Each voxel contains a compact direction dependent approximation of the appearance of the associated volumetric subpart of the model when viewed from a distance. The approximation is constructed by a visibility aware algorithm that fits parametric shaders to samples obtained by casting rays against the full resolution dataset. At rendering time, the volumetric structure, maintained off-core, is refined and rendered in front-to-back order, exploiting vertex programs for GPU evaluation of view-dependent voxel representations, hardware occlusion queries for culling occluded subtrees, and asynchronous I/O for detecting and avoiding data access latencies. Since the granularity of the multiresolution structure is coarse, data management, traversal and occlusion culling cost is amortized over many graphics primitives. The efficiency and generality of the approach is demonstrated with the interactive rendering of extremely complex heterogeneous surface models on current commodity graphics platforms.

Distributed visibility culling technique for complex scene rendering

This paper describes a complex scene rendering system that it can comprehensively render larger and more complex 3D scenes in a form of output-sensitive way by means of using distributed visibility culling technique. The process of the proposed visibility calculations is explicitly divided into two distinct phases, one is preprocessing stage, and the other is on-the-fly stage. At the preprocessing stage, the whole scene is partitioned into numerous regions, namely spatial cells, by adopting BSP tree algorithm. Accordingly, the complexity weight of each cell is estimated in advance depending on the number of geometric polygons within the cell. Afterwards we find out possible occluders in each cell for accelerating the real-time occlusion culling at run time. Moreover, instant visibility is taken into account to quickly calculate the tight potentially visible set (PVS) which is valid for several frames during the on-the-fly phase. As dynamic load balancing algorithm is concerned, we employ the cell arrangement mechanism to dynamically assign a specific amount of service demand to each calculating machine. The amount of service demand is estimated when a calculating machine is dynamically inserted into or removed from the distributed calculating cluster. Finally, after the drawing machines gather the PVS results from every calculating machine, they render the scene for users to view it on the next frames. From the simulation results, we can see that the proposed real-time walkthrough environment takes good advantage of the distributed visibility culling technique for displaying large, complex 3D scenes in real time and gets rid of a troublesome computation delay problem.

Occlusion culling and z-fail for soft shadow volume algorithms

This paper presents a significant improvement of our previously proposed soft shadow volume algorithm for simulating soft shadows. By restructuring the algorithm, we can considerably simplify the computations, introduce efficient occlusion culling with speedups of 3–4 times, thus approaching real-time performance. We can also generalize the algorithm to produce correct shadows even when the eye is inside a shadowed region (using z-fail). We present and evaluate a three pass implementation of the restructured algorithm for near real-time rendering of soft shadows on a computer with a commodity graphics accelerator. However, preferably the rendering of the wedges should be implemented in hardware, and for this we suggest and evaluate a single pass algorithm.

Layered point clouds: a simple and efficient multiresolution structure for distributing and rendering gigantic point-sampled models

We recently introduced an efficient multiresolution structure for distributing and rendering very large point sampled models on consumer graphics platforms [1]. The structure is based on a hierarchy of precomputed object-space point clouds, that are combined coarse-to-fine at rendering time to locally adapt sample densities according to the projected size in the image. The progressive block based refinement nature of the rendering traversal exploits on-board caching and object based rendering APIs, hides out-of-core data access latency through speculative prefetching, and lends itself well to incorporate backface, view frustum, and occlusion culling, as well as compression and view-dependent progressive transmission. The resulting system allows rendering of complex out-of-core models at high frame rates (over 60 M rendered points/second), supports network streaming, and is fundamentally simple to implement. We demonstrate the efficiency of the approach on a number of very large models, stored on local disks or accessed through a consumer level broadband network, including a massive 234 M samples isosurface generated by a compressible turbulence simulation and a 167 M samples model of Michelangelo's St. Matthew. Many of the details of our framework were presented in a previous study. We here provide a more thorough exposition, but also significant new material, including the presentation of a higher quality bottom-up construction method and additional qualitative and quantitative results.

Occlusion Culling in OpenSG PLUS

Very large polygonal models are frequently used in scientific computing, mechanical engineering, or virtual medicine. An effective technique to handle these large models is occlusion culling. Like most large model techniques, occlusion culling trades overhead costs with the rendering costs of the possibly occluded geometry. In this paper, we present occlusion culling techniques for OpenSG. These techniques utilize OpenGL or OpenGL extensions to determine occlusion information. Techniques utilizing image-space and temporal coherence are used to optimize occlusion query efficiency. Only the standard OpenSG data structures are used and no precomputation is necessary for the presented techniques.

Advanced techniques for high-quality multi-resolution volume rendering

We present several improvements for compression-based multi-resolution rendering of very large volume data sets at interactive to real-time frame rates on standard PC hardware. The algorithm accepts scalar or multi-variant data sampled on a regular grid as input. The input data are converted into a compressed hierarchical wavelet representation in a pre-processing step. During rendering, the wavelet representation is decompressed on-the-fly and rendered using hardware texture mapping. The level-of-detail used for rendering is adapted to the estimated screen-space error. To increase the rendering performance additional visibility tests, such as empty space skipping and occlusion culling, are applied. Furthermore, we discuss how to render the remaining multi-resolution blocks efficiently using modern graphics hardware. Using a prototype implementation of this algorithm we are able to perform a high-quality interactive rendering of large data sets on a single off-the-shelf PC.

Delay streams for graphics hardware

In causal processes decisions do not depend on future data. Many well-known problems, such as occlusion culling, order-independent transparency and edge antialiasing cannot be properly solved using the traditional causal rendering architectures, because future data may change the interpretation of current events.We propose adding a delay stream between the vertex and pixel processing units. While a triangle resides in the delay stream, subsequent triangles generate occlusion information. As a result, the triangle may be culled by primitives that were submitted after it. We show two-to fourfold efficiency improvements in pixel processing and video memory bandwidth usage in common benchmark scenes. We also demonstrate how the memory requirements of order-independent transparency can be substantially reduced by using delay streams. Finally, we describe how discontinuity edges can be detected in hardware. Previously used heuristics for collapsing samples in adaptive supersampling are thus replaced by connectivity information.

Ray space factorization for from-region visibility

From-region visibility culling is considered harder than from-point visibility culling, since it is inherently four-dimensional. We present a conservative occlusion culling method based on factorizing the 4D visibility problem into horizontal and vertical components. The visibility of the two components is solved asymmetrically: the horizontal component is based on a parameterization of the ray space, and the visibility of the vertical component is solved by incrementally merging umbrae. The technique is designed so that the horizontal and vertical operations can be efficiently realized together by modern graphics hardware. Similar to image-based from-point methods, we use an occlusion map to encode visibility; however, the image-space occlusion map is in the ray space rather than in the primal space. Our results show that the culling time and the size of the computed potentially visible set depend on the size of the viewcell. For moderate viewcells, conservative occlusion culling of large urban scenes takes less than a second, and the size of the potentially visible set is only about two times larger than the size of the exact visible set.

Immersive and Interactive Exploration of Billion-Atom Systems

We have developed a visualization system, namedAtomsviewer, to render a billion atoms from the results of a molecular dynamics simulation. This system uses a hierarchical view frustum culling algorithm based on the octree data structure to efficiently remove atoms that are outside of the field of view. A novel occlusion culling algorithm, using a probability function, then selects atoms with a high probability of being visible. These selected atoms are further tested with a traditional occlusion culling algorithm before being rendered as spheres at varying levels of detail. To achieve scalability, Atomsviewer is distributed over a cluster of PCs that execute a parallelized version of the hierarchical view frustum culling and the probabilistic occlusion culling, and a graphics workstation that renders the atoms. We have used Atomsviewer to render a billion-atom data set on a dual processor SGI Onyx2 with an InfiniteReality2 graphics pipeline connected to a four-node PC cluster.

Occlusion Culling Algorithms: A Comprehensive Survey

In this paper, occlusion culling techniques that appeared in the last decade are reviewed. Occlusion culling techniques are responsible for reducing the polygons rendered by the graphics hardware with the target of achieving real-time rendering. The various techniques are discussed in detail and a synopsis table with their main characteristics is given.

Visibility Driven Rasterization

We present a new visibility driven rasterization scheme that significantly increases the rendering performance of modern graphic subsystems. Instead of rasterizing, texturing, lighting, and depth‐testing each individual pixel, we introduce a two‐level visibility mask within the rasterization stage which facilitates the removal of groups of pixels and triangles from rasterization and subsequent pipeline stages.Local visibility information is stored within the visibility mask that is updated several times during the generation of a frame. The update can easily be accomplished by extending already available (in hardware) occlusion culling mechanisms (i.e. those of HP and SGI), where it is possible to integrate the additional functionality without any additional delay cycles. In addition to these existing hardware based occlusion culling approaches—which cull only geometry contained in bounding volumes determined as occluded—we are able to significantly accelerate the rendering of the geometry determined as visible. However, our approach does not specifically rely on such occlusion culling hardware.The proposed new rasterization scheme is well suited for hardware implementation, can easily be integrated into low‐cost rasterizers, and its scalability can vary upon available chip real estate. Only incremental modifications of modern graphics subsystems are required to achieve a significant improvement in rendering performance.

Occlusion Culling in Large Virtual Environments

In this paper, occlusion testing in very large virtual environments is discussed from two perspectives: a theoretical one, discussing occlusion culling in relation to detail elision (level of detail), and a practical one, relating to an adaptive occlusion-culling algorithm developed in this paper. The theoretical perspective formally demonstrates the efficiency of detail elision in the face of real-world-like environments. It further shows the utility of using detail elision not only to lower the triangle count of individual objects but also to lower the load on the scene graph traversal algorithm. Finally, the results indicate that, even in open environments, one needs occlusion culling and that approaches based on choosing only a few good (convex) occluders are insufficient in this case. Practically, the theoretical perspective is reflected in the development of an occlusion-culling algorithm based on a marriage of the frustum-slicing approach to view frustum culling and hierarchical occlusion maps (HOMs). The resulting algorithm is much simpler than the original HOM algorithm, requires little pre-processing, and integrates detail elision with the occlusion-culling algorithm in a natural way. The approach is well suited for use with large, complex models with a long mean free line of sight (“the great outdoors”), models for which it is not feasible to construct, or search, a database of occluders to be rendered in each frame. The algorithm is tested for such large models, and results show that frame rates tend to converge as the geometrical complexity of the model increases.

Instant Visibility

We present an online occlusion culling system which computes visibility in parallel to the rendering pipeline. We show how to use point visibility algorithms to quickly calculate a tight potentially visible set (PVS) which is valid for several frames, by shrinking the occluders used in visibility calculations by an adequate amount. These visibility calculations can be performed on a visibility server, possibly a distinct computer communicating with the display host over a local network. The resulting system essentially combines the advantages of online visibility processing and region-based visibility calculations, allowing asynchronous processing of visibility and display operations. We analyze two different types of hardware-based point visibility algorithms and address the problem of bounded calculation time which is the basis for true real-time behavior. Our results show reliable, sustained 60 Hz performance in a walkthrough with an urban environment of nearly 2 million polygons, and a terrain flyover.

LOD visibility culling and occluder synthesis

Level-of-detail occlusion culling is a novel approach to the management of occluders that can be easily integrated into most current visibility culling algorithms. The main contribution of this paper is an algorithm that automatically generates sets of densely overlapping boxes with enhanced occlusion properties from non-convex subsets. We call this method occluder synthesis because it is not sensitive to the way the objects are tesselated but to the space enclosed by them. The extension of this technique by allowing a bounded amount of image error is also discussed. We show that visibility computations can be based on a multiresolution model which provides several representations of these occluders with varying visibility accuracy. Our tests show that occlusion performance in tesselated scenes is improved severely even if no image-error is allowed.

Integrating Occlusion Culling and Levels of Detail through Hardly‐Visible Sets

Occlusion culling and level‐of‐detail rendering have become two powerful tools for accelerating the handling of very large models in real‐time visualization applications. We present a framework that combines both techniques to improve rendering times. Classical occlusion culling algorithms compute potentially visible sets (PVS), which are supersets of the sets of visible polygons. The novelty of our approach is to estimate the degree of visibility of each object of the PVS using synthesized coarse occluders. This allows to arrange the objects of each PVS into several Hardly‐Visible Sets (HVS) with similar occlusion degree. According to image accuracy and frame rate requirements, HVS provide a way to avoid sending to the graphics pipeline those objects whose pixel contribution is low due to partial occlusion. The image error can be bounded by the user at navigation time. On the other hand, as HVS offer a tighter estimation of the pixel contribution for each scene object, it can be used for a more convenient selection of the level‐of‐detail at which objects are rendered. In this paper, we describe the new framework technique, provide details of its implementation using a visibility octree as the chosen occlusion culling data structure and show some experimental results on the image quality.