Hierarchical level of detail optimization for constant frame rate rendering of radiosity scenes

The predictive hierarchical level of detail optimization algorithm of Mason and Blake is experimentally evaluated in the form of a practical application to hierarchical radiosity. In a novel approach the recursively subdivided patch hierarchy generated by a perceptually refined hierarchical radiosity algorithm is treated as a hierarchical level of detail scene description. In this way we use the Mason-Blake algorithm to successfully maintain constant frame rates during the interactive rendering of the radiosity-generated scene. We establish that the algorithm is capable of maintaining uniform frame rendering times, but that the execution time of the optimization algorithm itself is significant and is strongly dependent on frame-to-frame coherence and the granularity of the level of detail description. To compensate we develop techniques which effectively reduce and limit the algorithm execution time: We restrict the execution times of the algorithm to guard against pathological situations and propose simplification transforms that increase the granularity of the scene description, at minimal cost to visual quality. We demonstrate that using these techniques the algorithm is capable of maintaining interactive frame rates for scenes of arbitrary complexity. Furthermore we provide guidelines for the appropriate use of predictive level of detail optimization algorithms derived from our practical experience

A Low Dimensional Framework for Exact Polygon-to-Polygon Occlusion Queries

Despite the importance of from-region visibility computation in computer graphics, efficient analytic methods are still lacking in the general 3D case. Recently, different algorithms have appeared that maintain occlusion as a complex of polytopes in Plücker space. However, they suffer from high implementation complexity, as well as high computational and memory costs, limiting their usefulness in practice. In this paper, we present a new algorithm that simplifies implementation and computation by operating only on the skeletons of the polyhedra instead of the multi-dimensional face lattice usually used for exact occlusion queries in 3D. This algorithm is sensitive to complexity of the silhouette of each occluding object, rather than the entire polygonal mesh of each object. An intelligent feedback mechanism is presented that greatly enhances early termination by searching for apertures between query polygons. We demonstrate that our technique is several times faster than the state of the art

1 Applying Predictive Level of Detail

The predictive hierarchical level of detail optimization algorithm of Mason and Blake is experimentally evaluated in the form of a practical application to hierarchical radiosity. In a novel approach the recursively subdivided patch hierarchy generated by a perceptually refined hierarchical radiosity algorithm is treated as a hierarchical level of detail scene description. In this way we use the Mason-Blake algorithm to successfully maintain constant frame rates during the interactive rendering of the radiosity-generated scene. We establish that the algorithm is capable of maintaining uniform frame rendering times, but that the execution time of the optimization algorithm itself is significant and is strongly dependent on frame-to-frame coherence and the granularity of the level of detail description. To compensate we develop techniques which effectively reduce and limit the algorithm execution time: We restrict the execution times of the algorithm to guard against pathological situations and propose simplification transforms that increase the granularity of the scene description, at minimal cost to visual quality. We demonstrate that using these techniques the algorithm is capable of maintaining interactive frame rates for scenes of arbitrary complexity. Furthermore we provide guidelines for the appropriate use of predictive level of detail optimization algorithms derived from our practical experience

Hardware Accelerated Visibility Preprocessing using Adaptive Sampling Abstract

We present a novel aggressive visibility preprocessing technique for general 3D scenes. Our technique exploits commodity graphics hardware and is faster than most conservative solutions, while simultaneously not overestimating the set of visible polygons. The cost of this benefit is that of potential image error. In order to reduce image error, we have developed an effective error minimization heuristic. We present results showing the application of our technique to highly complex scenes, consisting of many small polygons. We give performance results, an in depth error analysis using various metrics, and an empirical analysis showing a high degree of scalability. We show that our technique can rapidly compute from-region visibility (1hr 19min for a 5 million polygon forest), with minimal error (0.3 % of image). On average 91.3 % of the scene is culled