Heuristics for ray tracing using space subdivision
The Visual Computer: International Journal of Computer Graphics
Octree-R: An Adaptive Octree for Efficient Ray Tracing
IEEE Transactions on Visualization and Computer Graphics
Theoretical and experimental aspects of ray shooting
Theoretical and experimental aspects of ray shooting
KD-tree acceleration structures for a GPU raytracer
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Introduction to real-time ray tracing
SIGGRAPH '05 ACM SIGGRAPH 2005 Courses
Interactive k-d tree GPU raytracing
Proceedings of the 2007 symposium on Interactive 3D graphics and games
A method for initialising the K-means clustering algorithm using kd-trees
Pattern Recognition Letters
Tracking Data Structures Coherency in Animated Ray Tracing: Kalman and Wiener Filters Approach
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
| Hi-index | 0.00 |
Many computer graphics rendering algorithms and techniques use ray tracing for generation of natural and photo-realistic images. The efficiency of the ray tracing algorithms depends, among other techniques, upon the data structures used in the background. kd-trees are some of the most commonly used data structures for accelerating ray tracing algorithms. Data structures using cost optimization techniques based upon Surface Area Heuristics (SAH) are generally considered to be best and of high quality. During the last decade, the trend has been moved from off-line rendering towards real time rendering with the introduction of high speed computers and dedicated Graphical Processing Units (GPUs). In this situation, SAH-optimized structures have been considered too slow to allow real-time rendering of complex scenes. Our goal is to demonstrate an accelerated approach in building SAH-based data structures to be used in real time rendering algorithms. The quality of SAH-based data structures heavily depends upon split-plane locations and the major bottleneck of SAH techniques is the time consumed to find those optimum split locations. We present a parabolic interpolation technique combined with a golden section search criteria for predicting kd-tree split plane locations. The resulted structure is 30% faster with 6% quality degradation as compared to a standard SAH approach for reasonably complex scenes with around 170k polygons.