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Raytracing Point Clouds Using Geometric Algebra

Deul, Crispin ; Burger, Michael ; Hildenbrand, Dietmar ; Koch, Andreas (2009)
Raytracing Point Clouds Using Geometric Algebra.
International Workshop on Computer Graphics, Computer Vision and Mathematics. Plzen, Czech Republic (01.-04.09.2009)
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Geometric Algebra (GA) supports the geometrically intuitive development of an algorithm with its build-in geometric primitives such as points, lines, spheres or planes. But on the negative side GA has a huge computational footprint. In this paper we study how GA can compete with traditional methods from Linear Algebra (LA) in the field of raytracing. We examine the raytracing algorithm for both GA and LA on the basis of primitive operations. Furthermore we introduce a novel framework for rendering point clouds based on spheres and planes as surface elements. We use this model to benchmark implementations of both algebras. Our results show that depending on the microprocessor architecture like CPUs, FPGAs or GPUs Geometric Algebra and Linear Algebra can raytrace with comparable speed.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2009
Autor(en): Deul, Crispin ; Burger, Michael ; Hildenbrand, Dietmar ; Koch, Andreas
Art des Eintrags: Bibliographie
Titel: Raytracing Point Clouds Using Geometric Algebra
Sprache: Englisch
Publikationsjahr: 2009
Veranstaltungstitel: International Workshop on Computer Graphics, Computer Vision and Mathematics
Veranstaltungsort: Plzen, Czech Republic
Veranstaltungsdatum: 01.-04.09.2009
Kurzbeschreibung (Abstract):

Geometric Algebra (GA) supports the geometrically intuitive development of an algorithm with its build-in geometric primitives such as points, lines, spheres or planes. But on the negative side GA has a huge computational footprint. In this paper we study how GA can compete with traditional methods from Linear Algebra (LA) in the field of raytracing. We examine the raytracing algorithm for both GA and LA on the basis of primitive operations. Furthermore we introduce a novel framework for rendering point clouds based on spheres and planes as surface elements. We use this model to benchmark implementations of both algebras. Our results show that depending on the microprocessor architecture like CPUs, FPGAs or GPUs Geometric Algebra and Linear Algebra can raytrace with comparable speed.

Freie Schlagworte: Forschungsgruppe Geometric Algebra Computing (GACO), Geometric algebra (GA), General Purpose Computation on Graphics Processing Unit (GPGPU), Point clouds, Field-programmable gate array (FPGA)
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Erstveröffentlichung; Konferenzeintrag

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Eingebettete Systeme und ihre Anwendungen
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
20 Fachbereich Informatik > Scientific Computing
20 Fachbereich Informatik > Simulation of multibody systems and deformable bodies
Hinterlegungsdatum: 26 Mär 2015 14:07
Letzte Änderung: 04 Mai 2022 13:05
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