We propose a new approach to collision and self-- collision detection of dynamically deforming objects that consist of tetrahedrons. Tetrahedral meshes are commonly used to represent volumetric deformable models and the presented algorithm is integrated in a physically--based environment, which can be used in game engines and surgical simulators. The proposed algorithm employs a hash function for compressing a potentially infinite regular spatial grid. Although the hash function does not always provide a unique mapping of grid cells, it can be generated very efficiently and does not require complex data structures, such as octrees or BSPs. We have investigated and optimized the parameters of the collision detection algorithm, such as hash function, hash table size and spatial cell size. The algorithm can detect collisions and self-- collisions in environments of up to 20k tetrahedrons in real--time. Although the algorithm works with tetrahedral meshes, it can be easily adapted to other object primitives, such as triangles.

Interactive environments for dynamically deforming objects play an important role in surgery simulation and entertainment technology. These environments require fast deformable models and very efficient collision handling techniques. While collision detection for rigid bodies is well-investigated, collision detection for deformable objects introduces additional challenging problems. This paper focusses on these aspects and summarizes recent research in the area of deformable collision detection. Various approaches based on bounding volume hierarchies, distance fields, and spatial partitioning are discussed. Further, image-space techniques and stochastic methods are considered. Applications in cloth modeling and surgical simulation are presented.

Image-space techniques have shown to be very efficient for collision detection in dynamic simulation and animation environments. This paper proposes a new image-space technique for efficient collision detection of arbitrarily shaped, water-tight objects. In contrast to existing approaches that do not consider self-collisions, our approach combines the image-space object representation with information on face orientation to overcome this limitation. While

Abstract — We present an approach to visualizing particlebased simulation data using interactive ray tracing, and describe an algorithmic enhancement that exploits the properties of these datasets to provide highly interactive performance and reduced storage requirements. This algorithm for fast packet-based ray tracing of multi-level grids enables interactive visualization of large, time-varying datasets with millions of particles and incorporates advanced features like soft shadows. We compare the performance of our approach with two recent particle visualization systems: one based on an optimized single ray grid traversal algorithm, the other on programmable graphics hardware. This comparison demonstrates that the new algorithm offers an attractive alternative for interactive particle visualization. Index Terms — Particle visualization, interactive ray tracing, coherent grid traversal, large and time-varying particle datasets I.