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.

We introduce the Bounded Deformation Tree, or BD-Tree, which can perform collision detection with reduced deformable models at costs comparable to collision detection with rigid objects. Reduced deformable models represent complex deformations as linear superpositions of arbitrary displacement fields, and are used in a variety of applications of interactive computer graphics. The BD-Tree is a bounding sphere hierarchy for output-sensitive collision detection with such models. Its bounding spheres can be updated after deformation in any order, and at a cost independent of the geometric complexity of the model; in fact the cost can be as low as one multiplication and addition per tested sphere, and at most linear in the number of reduced deformation coordinates. We show that the BDTree is also extremely simple to implement, and performs well in practice for a variety of real-time and complex off-line deformable simulation examples.

The most significant deficiency of most of today’s interactive ray tracers is that they are restricted to static walkthroughs. This restriction is due to the static nature of the acceleration structures used. While the best reported frame rates for static geometric models have been achieved using carefully constructed kd-trees, this article shows that bounding volume hierarchies (BVHs) can be used to efficiently ray trace large static models. More importantly, the BVH can be used to ray trace deformable models (sets of triangles whose positions change over time) with little loss of performance. A variety of efficiency techniques are used to achieve this performance, but three algorithmic changes to the typical BVH algorithm are mainly responsible. First, the BVH is built using a variant of the surface area heuristic conventionally used to build kd-trees. Second, the topology of the BVH is not changed over time so that only the bounding volumes need to be refit from frame-to-frame. Third, and most importantly, packets of rays are traced together through the BVH using a novel integrated packet-frustum traversal scheme. This traversal scheme elegantly combines the advantages of both packet traversal and frustum traversal and allows for rapid hierarchy descent for packets that hit bounding volumes as well as rapid exits for packets that miss. A BVH-based ray tracing system using these techniques is shown to achieve performance for deformable models comparable to that previously available only for static models.

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.

Figure 1: Dress simulation: Four different images of a 210 step sequence taken from a dynamic cloth simulation and consisting of 40K triangles. By updating in real-time instead of rebuilding the BVH of the deforming model according to our heuristic, we are able to render the animation at 13 frames per second with 512 2 screen resolution using a dual-core P4 processor at 2.8 GHz. We present an efficient approach for interactive ray tracing of deformable or animated models. Unlike many of the recent approaches for ray tracing static scenes, we use bounding volume hierarchies (BVHs) instead of kd-trees as the underlying acceleration structure. Our algorithm makes no assumptions about the simulation or the motion of objects in the scene and dynamically updates or recomputes the BVHs. We also describe a method to detect BVH quality degradation during the simulation in order to determine when the hierarchy needs to be rebuilt. Furthermore, we show that the ray coherence techniques introduced for kd-trees can be naturally extended to BVHs and yield similar improvements. Finally, we compare BVHs to spatial kd-trees, which have been used recently as a replacement for AABB hierarchies. Our algorithm has been applied to different scenarios arising in animation and simulation and consisting of tens of thousands to a million triangles. In practice, our system can ray trace these models at 3-13 frames a second on a desktop PC including secondary rays.

This paper introduces a fast continuous collision detection technique for polyhedral rigid bodies. As opposed to most collision detection techniques, the computation of the first contact time between two objects is inherently part of the algorithm. The method can thus robustly prevent objects interpenetrations or collisions misses, even when objects are thin or have large velocities. The method is valid for general objects (polygon soups), handles multiple moving objects and acyclic articulated bodies, and is efficient in low and high coherency situations. Moreover, the method can be used to speed up existent continuous collision detection methods for parametric or implicit rigid surfaces. The collision detection algorithms have been successfully coupled to a real-time dynamics simulator. Various experiments are conducted that show the method’s ability to produce high-quality interaction (precise objects positioning for example) between models up to tens of thousands of triangles, which couldn’t have been performed with previous continuous methods. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Animation- Virtual Reality 1.

Fast and accurate collision detection between geometric bodies is essential in application areas like virtual reality, animation, simulation, games and robotics. In this work, we address the collision detection problem in applications where deformable bodies are used, which change their overall shape every time step of the simulation. We propose and evaluate suitable bounding volume trees for deforming bodies that can be pre-built and then updated very efficiently during simulation. Several heuristics for updating the trees due to deformations are compared to each other. By combining a top-down and a bottom-up update strategy into a hybrid tree update method, promising results were achieved. Experiments show that our approach is four to five times faster than a previously leading method.

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

We present a novel bounding volume hierarchy that allows for extremely small data structure sizes while still performing collision detection as fast as other classical hierarchical algorithms in most cases. The hierarchical data structure is a variation of axis-aligned bounding box trees. In addition to being very memory efficient, it can be constructed efficiently and very fast. We also propose

In recent years, thanks to the increasing computational power available, real time computer animation has naturally evolved to model more complex and computationally expensive scenes. Consequently, all the problems concerning physical modelling need further research to tackle these new requirements, especially the problem of collision detection for deformable objects. Most existing solutions cannot not be trivially extended, because they are strongly based on the assumption that the shape of the object is fixed. In this paper we propose a general approach to reduce the cost of collision detection between deformable objects explicitly represented, regardless of the specific geometrical and physical manner in which they are modelled.