B-KD trees for hardware accelerated ray tracing of dynamic scenes

Woop, Sven; Marmitt, Gerd; Slusallek, Philipp

doi:10.1145/1283900.1283912

Cited by 52 publications

(43 citation statements)

References 33 publications

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“…Around the same time, a similar structure was proposed by Woop et al (the B-KD tree, [35]). The main benefit of these algorithms is the fast build time: Where a kDtree for ∼200k triangles typically takes seconds, a BIH for the same scene is built in a fraction of a second.…”

Section: Bounding Interval Hierarchymentioning

confidence: 86%

Real-time Ray Tracing through the Eyes of a Game Developer

Bikker¹

2007

2007 IEEE Symposium on Interactive Ray Tracing

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Figure 1: Real-time ray traced images from our experimental ARAUNA engine, used in a student project. ABSTRACTThere has been and is a tremendous amount of research on the topic of ray tracing, spurred by the relatively recent advent of real-time ray tracing and the inevitable appearance of consumer hardware capable of handling this rendering algorithm. Besides researchers, the prospect of a brave new world attracts hobbyists (such as demo coders) and game developers: Ray tracing promises an elegant and fascinating alternative to z-buffer approaches, as well as more intuitive graphics and games development. This article provides a view from the inside on ray tracing in games and demos, where the emphasis is on performance and short-term practical usability. It covers the way science is applied, the unique contribution of these developers to the field and their link with the research community.The Arauna ray tracer, developed at the NHTV university of applied science, is used as an example of a ray tracer that has been specifically build with games and performance in mind. Its purpose and architecture, as well as some implementation details are presented.

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Section: Bounding Interval Hierarchymentioning

confidence: 86%

Real-time Ray Tracing through the Eyes of a Game Developer

Bikker¹

2007

2007 IEEE Symposium on Interactive Ray Tracing

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“…This reduces the memory requirements from storing 6 to 2 coordinates only. Similarly, Woop et al [40] present a hardware implementation called the bkd-tree in which they store the left and right bounds for both children and therefore use 4 coordinates per node. Construction for both structures is almost identical to BVHs by just storing the respective bounding box coordinates.…”

Section: Comparison To Spatial Kd-treesmentioning

confidence: 99%

RT-DEFORM: Interactive Ray Tracing of Dynamic Scenes using BVHs

Lauterbach

Yoon

Tuft

et al. 2006

2006 IEEE Symposium on Interactive Ray Tracing

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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.

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“…We refer to this second task as sifting. Note that for a kd-tree, a single AABB may be copied into both children, so sifting is more complex for a kd-tree than a B-KD tree [24,18]. Our sifting implementation uses two important optimizations.…”

Section: Additional Optimizationsmentioning

confidence: 99%

“…However, the techniques described in this paper are directly applicable to the construction of other high-quality acceleration structures based on the surface area heuristic. Examples include SAH-optimized bounding-volume hierarchies [20] and B-KD trees [24,18]. The most important conclusion from this paper is that acceleration structures for interactive ray tracers can and should be built using a good approximation to the SAH.…”

Section: Introductionmentioning

confidence: 99%

Fast kd-tree Construction with an Adaptive Error-Bounded Heuristic

Hunt

Mark

Stoll

2006

2006 IEEE Symposium on Interactive Ray Tracing

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Construction of effective acceleration structures for ray tracing is a well studied problem. The highest quality acceleration structures are generally agreed to be those built using greedy cost optimization based on a surface area heuristic (SAH). This technique is most often applied to the construction of kd-trees, as in this work, but is equally applicable to the construction of other hierarchical acceleration structures. Unfortunately, SAH-optimized data structure construction has previously been too slow to allow per-frame rebuilding for interactive ray tracing of dynamic scenes, leading to the use of lower-quality acceleration structures for this application. The goal of this paper is to demonstrate that high-quality SAH based acceleration structures can be constructed quickly enough to make them a viable option for interactive ray tracing of dynamic scenes.We present a scanning-based algorithm for choosing kd-tree split planes that are close to optimal with respect to the SAH criteria. Our approach approximates the SAH cost function across the spatial domain with a piecewise quadratic function with bounded error and picks minima from this approximation. This algorithm takes full advantage of SIMD operations (e.g., SSE) and has favorable memory access patterns. In practice this algorithm is faster than sorting-based SAH build algorithms with the same asymptotic time complexity, and is competitive with non-SAH build algorithms which produce lower-quality trees. The resulting trees are almost as good as those produced by a sorting-based SAH builder as measured by ray tracing time. For a test scene with 180k polygons our system builds a high-quality kd-tree in 0.26 seconds that only degrades ray tracing time by 3.6% compared to a full quality tree.

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B-KD trees for hardware accelerated ray tracing of dynamic scenes

Cited by 52 publications

References 33 publications

Real-time Ray Tracing through the Eyes of a Game Developer

Real-time Ray Tracing through the Eyes of a Game Developer

RT-DEFORM: Interactive Ray Tracing of Dynamic Scenes using BVHs

Fast kd-tree Construction with an Adaptive Error-Bounded Heuristic

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