Hierarchical Radiosity Algorithm Research Articles

Hierarchical Radiosity for Multiresolution Systems Based on Normal Tests

The hierarchical radiosity algorithm provides high-quality illumination and the view-independent results obtained can be re-employed for different camera positions. On the other hand, the utilization of multiresolution models is a common solution for the real-time rendering of complex scenes. In this case, the level of detail of each object depends on the specific camera position. Unfortunately, global illumination computations may present an important performance loss in this context. In this paper we present a new solution for hierarchical radiosity for multiresolution systems. Our proposal is based on the application of an enriched hierarchical radiosity algorithm to an input scene with low-resolution objects (represented by coarse meshes) and the efficient data management of the resulting values. The representation of the information we use permits the application of the radiosity values obtained for the coarse version of an object to finer resolution versions of that object. Results of our implementation show that our algorithm produces high-quality images with an important reduction in computational costs.

Task Pool Teams: a hybrid programming environment for irregular algorithms on SMP clusters

Clusters of symmetric multiprocessors (SMPs) are popular platforms for parallel programming since they provide large computational power for a reasonable price. For irregular application programs with dynamically changing computation and data access behavior, a flexible programming model is needed to achieve efficiency. In this paper we propose Task Pool Teams as a hybrid parallel programming environment to realize irregular algorithms on clusters of SMPs. Task Pool Teams combine task pools on single cluster nodes by an explicit message passing layer. They offer load balance together with multi-threaded, asynchronous communication. Appropriate communication protocols and task pool implementations are provided and accessible by an easy-to-use application programmer interface. As application examples we present a branch and bound algorithm and the hierarchical radiosity algorithm. Copyright © 2006 John Wiley & Sons, Ltd.

Texture-based visibility for efficient lighting simulation

Lighting simulations using hierarchical radiosity with clustering can be very slow when the computation of fine and artifact-free shadows is needed. To avoid the high cost of mesh refinement associated with fast variations of visibility across receivers, we propose a new hierarchical algorithm in which partial visibility maps can be computed on the fly, using a convolution technique for emitter-receiver configurations where complex shadows are produced. Other configurations still rely on mesh subdivision to reach the desired accuracy in modeling energy transfer. In our system, therefore, radiosity is represented as a combination of textures and piecewise-constant or linear contributions over mesh elements at multiple hierarchical levels. We give a detailed description of the gather , push / pull , and display stages of the hierarchical radiosity algorithm, adapted to seamlessly integrate both representations. A new refinement algorithm is proposed, which chooses the most appropriate technique to compute the energy transfer and resulting radiosity distribution for each receiver/transmitter configuration. Comprehensive error control is achieved by subdividing either the source or receiver in a traditional manner, or by using a blocker subdivision scheme that improves the quality of shadow masks without increasing the complexity of the mesh. Results show that high-quality images are obtained in a matter of seconds for scenes with tens of thousands of polygons.

Partitioning and Scheduling Large Radiosity Computations in Parallel

We show, in this paper, how it is feasible to efficiently perform large radiosity computations on a conventional (distributed) shared memory multiprocessor machine. Hierarchical radiosity algorithms, although computationally expensive, are an efficient view-independent way to compute the global illumination which gives the visual ambiance to a scene. Their effective parallelization is made challenging, however, by their non-uniform, dynamically changing characteristics, and their need for long-range communication. To address this need, we have developed appropriate partitioning and scheduling techniques, that deliver an optimal load balancing, while still exhibiting excellent data locality. We provide the detailed implementation of these techniques and present results of experiments showing very good acceleration and scalability performances. The accurate radiosity solutions required to render high quality images of an extremely large model are computed in a reasonable time. The rendering capabilities of modern graphics hardware are then used to visualize this virtual pre-lit environment in real-time: a two minutes QuickTime movie example can be downloaded from our site: ftp://ftp.loria.fr/pub/loria/isa/Cavin/sodaHallWalk.qt.gz (last accessable in 2000)

Interactive virtual relighting of real scenes

Computer augmented reality (CAR) is a rapidly emerging field which enables users to mix real and virtual worlds. Our goal is to provide interactive tools to perform common illumination, i.e., light interactions between real and virtual objects, including shadows and relighting (real and virtual light source modification). In particular, we concentrate on virtually modifying real light source intensities and inserting virtual lights and objects into a real scene; such changes can be very useful for virtual lighting design and prototyping. To achieve this, we present a three-step method. We first reconstruct a simplified representation of real scene geometry using semiautomatic vision-based techniques. With the simplified geometry, and by adapting recent hierarchical radiosity algorithms, we construct an approximation of real scene light exchanges. We next perform a preprocessing step, based on the radiosity system, to create unoccluded illumination textures. These replace the original scene textures which contained real light effects such as shadows from real lights. This texture is then modulated by a ratio of the radiosity (which can be changed) over a display factor which corresponds to the radiosity for which occlusion has been ignored. Since our goal is to achieve a convincing relighting effect, rather than an accurate solution, we present a heuristic correction process which results in visually plausible renderings. Finally, we perform an interactive process to compute new illumination with modified real and virtual light intensities.

Synchronisation and Load Balancing for Parallel Hierarchical Radiosity of Complex Scenes on a Heterogeneous Computer Network

In this paper we propose a SPMD parallel hierarchical radiosity algorithm relying on a novel partitioning method which may apply to any kind of architectural scene. This algorithm is based on MPI (Message Passing Interface), a communication library which allows the use of either a heterogeneous set of concurrent computers or a parallel computer or both. The database is stored on a common directory and accessed by all the processors (through NFS in case of a network of computers). As the objective is to handle complex scenes such as building interiors, to cope with the problem of memory size, only a subset of the database resides in memory of each processor. This subset is determined with the help of a partitioning into 3D cells, clustering and visibility calculations. A graph expressing visibility between the resulting clusters is determined, partitioned (with a new method based on classification of K‐means type) and distributed amongst all the processors. Each processor is responsible for gathering energy (using the Gauss‐Seidel method) only for its subset of clusters. In order to reduce the disk transfers due to downloading these subsets of clusters, we use an ordering strategy based on the traveling salesman algorithm. Dynamic load balancing relies on a task stealing approach while termination is detected by configuring the processors into a ring and moving a token around this ring. The parallel iterative resolution is of group iterative type. Its mathematical convergence is proven in the appendix.

A system subdivision approach for large radiosity computation

(n) for n subsystems. Moreover, the data necessary for each subsystem computation is completely localized, which allows the database to be stored on disk. The algorithm can easily be implemented with a slight modification of the hierarchical radiosity algorithm. Experiments demonstrate the efficiency of the algorithm.

Tighter error bounds and weighted error metrics for hierarchical radiosity

In this paper we first derive a tighter error bound on form factors as a subdivision criterion for the hierarchical radiosity algorithm. Such an error bound can reduce more unnecessary links and improve the performance of the hierarchical radiosity algorithm to meet a user-specified error tolerance. We then propose a weighted error metric in form factor computation such that more effort is automatically applied to shadow boundaries. Evaluating form factors along shadow boundaries with a higher degree of precision should enhance the quality of human perception. Using the proposed tighter error bound on the weighted error metric, we not only improve the performance but also increase the accuracy of the hierarchical radiosity algorithm. © 1998 John Wiley & Sons, Ltd.

Using Subdivision on Hierarchical Data to Reconstruct Radiosity Distribution

Computing global illumination by finite element techniques usually generates a piecewise constant approximation of the radiosity distribution on surfaces. Directly displaying such scenes generates artefacts due to discretization errors. We propose to remedy this drawback by considering the piecewise constant output to be samples of a (piecewise) smooth function in object space and reconstruct this function by applying a binary subdivision scheme. We design custom taylored subdivision schemes with quadratic precision for the efficient refinement of cell‐ or pixel‐type data. The technique naturally allows to reconstruct functions from non‐uniform samples which result from adaptive binary splitting of the original domain (quadtree). This type of output is produced, e.g., by hierarchical radiosity algorithms. The result of the subdivision process can be mapped as a texture on the respective surface patch which allows to exploit graphics hardware for considerably accelerating the display.

Using Subdivision on Hierarchical Data to Reconstruct Radiosity Distribution

Computing global illumination by finite element techniques usually generates a piecewise constant approximation of the radiosity distribution on surfaces. Directly displaying such scenes generates artefacts due to discretization errors. We propose to remedy this drawback by considering the piecewise constant output to be samples of a (piecewise) smooth function in object space and reconstruct this function by applying a binary subdivision scheme. We design custom taylored subdivision schemes with quadratic precision for the efficient refinement of cell‐ or pixel‐type data. The technique naturally allows to reconstruct functions from non‐uniform samples which result from adaptive binary splitting of the original domain (quadtree). This type of output is produced, e.g., by hierarchical radiosity algorithms. The result of the subdivision process can be mapped as a texture on the respective surface patch which allows to exploit graphics hardware for considerably accelerating the display.

Parallel visualization algorithms: performance and architectural implications

Recently, a new class of scalable, shared-address-space multiprocessors has emerged. Like message-passing machines, these multiprocessors have a distributed interconnection network and physically distributed main memory. However, they provide hardware support for efficient implicit communication through a shared address space, and they automatically exploit temporal locality by caching both local and remote data in a processor's hardware cache. In this article, we show that these architectural characteristics make it much easier to obtain very good speedups on the best known visualization algorithms. Simple and natural parallelizations work very well, the sequential implementations do not have to be fundamentally restructured, and the high degree of temporal locality obviates the need for explicit data distribution and communication management. We demonstrate our claims through parallel versions of three state-of-the-art algorithms: a recent hierarchical radiosity algorithm by Hanrahan et al. (1991), a parallelized ray-casting volume renderer by Levoy (1992), and an optimized ray-tracer by Spach and Pulleyblank (1992). We also discuss a new shear-warp volume rendering algorithm that provides the first demonstration of interactive frame rates for a 256/spl times/256/spl times/256 voxel data set on a general-purpose multiprocessor. >

A rapid hierarchical radiosity algorithm

This paper presents a rapid hierarchical radiosity algorithm for illuminating scenes containing large polygonal patches. The algorithm constructs a hierarchical representation of the form factor matrix by adaptively subdividing patches into subpatches according to a user-supplied error bound. The algorithm guarantees that all form factors are calculated to the same precision, removing many common image artifacts due to inaccurate form factors. More importantly, the algorithm decomposes the form factor matrix into at most O(n ) blocks (where n is the number of elements). Previous radiosity algorithms represented the element-to-element transport interactions with n 2 form factors. Visibility algorithms are given that work well with this approach. Standard techniques for shooting and gathering can be used with the hierarchical representation to solve for equilibrium radiosities, but we also discuss using a brightness-weighted error criteria, in conjunction with multigridding, to even more rapidly progressively refine the image.