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| Daniel Fontijne, Leo Dorst, "Modeling 3D Euclidean Geometry," IEEE Computer Graphics and Applications, vol. 23, no. 2, pp. 68-78, March/April, 2003. | |||
| BibTex | x | ||
| @article{ 10.1109/MCG.2003.1185582, author = {Daniel Fontijne and Leo Dorst}, title = {Modeling 3D Euclidean Geometry}, journal ={IEEE Computer Graphics and Applications}, volume = {23}, number = {2}, issn = {0272-1716}, year = {2003}, pages = {68-78}, doi = {http://doi.ieeecomputersociety.org/10.1109/MCG.2003.1185582}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - IEEE Computer Graphics and Applications TI - Modeling 3D Euclidean Geometry IS - 2 SN - 0272-1716 SP68 EP78 EPD - 68-78 A1 - Daniel Fontijne, A1 - Leo Dorst, PY - 2003 VL - 23 JA - IEEE Computer Graphics and Applications ER - | |||
Computations of 3D Euclidean geometry can be performed using various computational models of different effectiveness. In this article, the authors compare five alternatives: 3D linear algebra, 3D geometric algebra, a mix of 4D homogeneous coordinates and Pl?cker coordinates, a 4D homogeneous model using geometric algebra, and the 5D conformal model using geometric algebra. Higher dimensional models and models using geometric algebra can express geometric primitives, computations, and constructions more elegantly, but this elegance might come at a performance penalty. The authors explore these issues using the implementation of a simple ray tracer as a practical goal and guide and show how to implement the most important geometric computations of the ray-tracing algorithm using each of the five models as well as benchmark each implementation.
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