On quality metrics of bounding volume hierarchies

Aila, Timo; Karras, Tero; Laine, Samuli

doi:10.1145/2492045.2492056

Cited by 36 publications

(26 citation statements)

References 14 publications

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“…However, regarding the trace speed, the best performance was achieved by ATRBVH for three test scenes, while in other six cases the k-means-based methods achieved the highest trace speed. While this can partly be caused by the view dependency of the measurements, it also corresponds to recent observation of Aila et al [1] that the SAH cost alone need not precisely reflect the trace speeds on the GPU.…”

Section: Resultssupporting

confidence: 64%

“…Bittner and Havran [6] proposed modifying SAH by including the actual ray distribution, Feltman et al [11] extended this idea to shadow rays. Corrections of the SAH-based BVH quality metrics have been proposed by Aila et al [1].…”

Section: Related Workmentioning

confidence: 99%

“…B Daniel Meister meistdan@fel.cvut.cz 1 Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic graphics as they help to handle the ever-increasing scene complexity. The bounding volume hierarchies (BVH), which we address in the paper, have been shown to accelerate a number of intersection queries, particularly in the context of collision detection and ray tracing.…”

Section: Introductionmentioning

confidence: 99%

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Parallel BVH construction using k-means clustering

Meister

Bittner

2016

Vis Comput

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We propose a novel method for fast parallel construction of bounding volume hierarchies (BVH) on the GPU. Our method is based on a combination of divisible and agglomerative clustering. We use the k-means algorithm to subdivide scene primitives into clusters. From these clusters, we construct treelets using the agglomerative clustering algorithm. Applying this procedure recursively, we construct the entire bounding volume hierarchy. We implemented the method using parallel programming concepts on the GPU. The results show the versatility of the method: it can be used to construct medium-quality hierarchies very quickly, but also it can be used to construct high-quality hierarchies given a slightly longer computational time. We evaluate the method in the context of GPU ray tracing and show that it provides results comparable with other state-of-the-art GPU techniques for BVH construction. We also believe that our approach based on the k-means algorithm gives a new insight into how bounding volume hierarchies can be constructed.

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Section: Resultssupporting

confidence: 64%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Parallel BVH construction using k-means clustering

Meister

Bittner

2016

Vis Comput

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“…However, the SAH estimate is not a perfect indicator of ray casting performance. Aila et al [2013] propose a new metric as an extension to SAH, which better reects ray casting performance.…”

Section: Bounding Volume Hierarchymentioning

confidence: 99%

Sequential Monte Carlo instant radiosity

Hedman

Karras

Lehtinen

2016

Proceedings of the 20th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games

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The focus of this thesis is to accelerate the synthesis of physically accurate images using computers.Such images are generated by simulating how light ows in the scene using unbiased Monte Carlo algorithms. To date, the eciency of these algorithms has been too low for real-time rendering of error-free images. This limits the applicability of physically accurate image synthesis in interactive contexts, such as pre-visualization or video games.We focus on the well-known Instant Radiosity algorithm by Keller [1997], that approximates the indirect light eld using virtual point lights (VPLs). This approximation is unbiased and has the characteristic that the error is spread out over large areas in the image. This low-frequency noise manifests as an unwanted ickering eect in image sequences if not kept temporally coherent.Currently, the limited VPL budget imposed by running the algorithm at interactive rates results in images which may noticeably dier from the ground-truth.We introduce two new algorithms that alleviate these issues. The rst, clustered hierarchical importance sampling, reduces the overall error by increasing the VPL budget without incurring a signicant performance cost. It uses an unbiased Monte Carlo estimator to estimate the sensor response caused by all VPLs. We reduce the variance of this estimator with an ecient hierarchical importance sampling method. The second, sequential Monte Carlo Instant Radiosity, generates the VPLs using heuristic sampling and employs non-parametric density estimation to resolve their probability densities. As a result the algorithm is able to reduce the number of VPLs that move between frames, while also placing them in regions where they bring light to the image. This increases the quality of the individual frames while keeping the noise temporally coherent and less noticeable between frames.When combined, the two algorithms form a rendering system that performs favourably against traditional path tracing methods, both in terms of performance and quality. Unlike prior VPLbased methods, our system does not suer from the objectionable lack of temporal coherence in highly occluded scenes.

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“…These approaches allow to decrease the expected cost of a BVH beyond the cost achieved by the traditional top down approach. The comparison of different BVH construction methods and new quality metrics have been studied recently by Aila et al [24].…”

Section: Related Workmentioning

confidence: 99%