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Tracking Data Structures Coherency in Animated Ray Tracing: Kalman and Wiener Filters Approach
Ansvarig organisation
2008 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat) Published
Abstract [en]

The generation of natural and photorealistic images in computer graphics, normally make use of a well known method called ray tracing. Ray tracing is being adopted as a primary image rendering method in the research community for the last few years. With the advent of todays high speed processors, the method has received much attention over the last decade. Modern power of GPUs/CPUs and the accelerated data structures are behind the success of ray tracing algorithms. kd-tree is one of the most widely used data structures based on surface area heuristics (SAH). The major bottleneck in kd-tree construction is the time consumed to find optimum split locations. In this paper, we propose a prediction algorithm for animated ray tracing based on Kalman and Wiener filters. Both the algorithms successfully predict the split locations for the next consecutive frame in the animation sequence. Thus, giving good initial starting points for one dimensional search algorithms to find optimum split locations – in our case parabolic interpolation combined with golden section search. With our technique implemented, we have reduced the “running kd-tree construction” time by between 78% and 87% for dynamic scenes with 16.8K and 252K polygons respectively.

Ort, förlag, år, upplaga, sidor
Berlin/Heideberg: Spinger-Verlag , 2008.
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Datavetenskap (datalogi)
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URN: urn:nbn:se:bth-8298DOI: 10.1007/978-3-540-89639-5ISI: 000264057800105Lokalt ID: oai:bth.se:forskinfo01D8E0ED47D7A298C125751B00391BA2ISBN: 978-3-540-89638-8 (tryckt)OAI: oai:DiVA.org:bth-8298DiVA, id: diva2:836005
Konferens
Proc. of the Fourth International Symposium on Advances in Visual Computing (ISVC 2008)
Anmärkning
Lecture Notes in Computer Science No. 5358Tillgänglig från: 2012-09-18 Skapad: 2008-12-10 Senast uppdaterad: 2018-02-02Bibliografiskt granskad

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Totalt: 68 träffar
RefereraExporteraLänk till posten
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