Publikace

We propose a new adaptive algorithm for determining virtual point lights (VPL) in the scope of real-time instant radiosity methods, which use a limited number of VPLs. The proposed method is based on Metropolis-Hastings sampling and exhibits better temporal coherence of VPLs, which is particularly important for real-time applications dealing with dynamic scenes. We evaluate the properties of the proposed method in the context of the algorithm based on imperfect shadow maps and compare it with the commonly used inverse transform method. The results indicate that the proposed technique can significantly reduce the temporal flickering artifacts even for scenes with complex materials and textures. Further, we propose a novel splatting scheme for imperfect shadow maps using hardware tessellation. This scheme significantly improves the rendering performance particularly for complex and deformable scenes. We thoroughly analyze the performance of the proposed techniques on test scenes with detailed materials, moving camera, and deforming geometry.

We present an algorithm for fast optimization of bounding volume hierarchies (BVH) for efficient ray tracing. We perform selective updates of the hierarchy driven by the cost model derived from the surface area heuristic. In each step, the algorithm updates a fraction of the hierarchy nodes to minimize the overall hierarchy cost. The updates are realized by simple operations on the tree nodes: removal, search and insertion. Our method can quickly reduce the cost of the hierarchy constructed by the traditional techniques, such as the surface area heuristic. We evaluate the properties of the proposed method on fourteen test scenes of different complexity including individual objects and architectural scenes. The results show that our method can improve a BVH initially constructed with the surface area heuristic by up to 27% and a BVH constructed with the spatial median split by up to 88%.

We present a novel method for massively parallel hierarchical scene processing on the GPU, which is based on sequential decomposition of the given hierarchical algorithm into small functional blocks. The computation is fully managed by the GPU using a specialized task pool which facilitates synchronization and communication of processing units. We present two applications of the proposed approach: construction of the bounding volume hierarchies and collision detection based on divide-and-conquer ray tracing. The results indicate that using our approach we achieve high utilization of the GPU even for complex hierarchical problems which pose a challenge for massive parallelization.

Finding minimal cuts on graphs with a grid-like structure has become a core task for solving many computer vision and graphics related problems. However, computation speed and memory consumption oftentimes limit the effective use in applications requiring high resolution grids or interactive response. In particular, memory bandwidth represents one of the major bottlenecks even in today's most efficient implementations. We propose a compact data structure with cache-efficient memory layout for the representation of graph instances that are based on regular N-D grids with topologically identical neighborhood systems. For this common class of graphs our data structure allows for 3 to 12 times higher grid resolutions and a 3- to 9-fold speedup compared to existing approaches. Our design is agnostic to the underlying algorithm, and hence orthogonal to other optimizations such as parallel and hierarchical processing. We evaluate the performance gain on a variety of typical problems including 2D/3D segmentation, colorization, and stereo. All experiments show an unconditional improvement in terms of speed and memory consumption, with graceful performance degradation for graphs with increasing topological irregularities.

We present ‘Smart Scribbles’—a new scribble-based interface for user-guided segmentation of digital sketchy drawings. In contrast to previous approaches based on simple selection strategies, Smart Scribbles exploits richer geometric and temporal information, resulting in a more intuitive segmentation interface. We introduce a novel energy minimization formulation in which both geometric and temporal information from digital input devices is used to define stroke-to-stroke and scribble-to-stroke relationships. Although the minimization of this energy is, in general, an NP-hard problem, we use a simple heuristic that leads to a good approximation and permits an interactive system able to produce accurate labellings even for cluttered sketchy drawings. We demonstrate the power of our technique in several practical scenarios such as sketch editing, as-rigid-as-possible deformation and registration, and on-the-fly labelling based on pre-classified guidelines.

The minimization of traversal cost using surface area heuristic is extensively used to build high quality spatial subdivisions and bounding volume hierarchies for ray tracing. Despite the fair performance of trees built with the cost model, it is known that the underlying assumptions for surface area heuristics are not realistic. In this paper we show how the cost function of the surface area heuristic can be improved on using the assumed visibility of geometric primitives such as triangles. This way the build algorithm utilizes the exact or assumed visibility to construct more efficient BVHs by traversing smaller portion of the hierarchy. We show that by these inexpensive modifications to the cost function we can speed up the ray traversal by approximately 102% on average for path tracing of highly occluded scenes compared to standard surface area heuristics. Moreover, it is also possible to lower the construction time and memory usage by subdividing only those parts of the animated scene through which rays are expected to be traversed.