A MULTIAGENT ARCHITECTURE FOR 3D RENDERING OPTIMIZATION

  • Authors:
  • Carlos Gonzalez-Morcillo;Gerhard Weiss;David Vallejo;Luis Jimenez-Linares;Jose Jesus Castro-Schez

  • Affiliations:
  • Escuela Superior de Informatica, Paseo de la Universidad, Ciudad Real, Spain,Software Competence Center GmbH, Hagenberg, Austria;Software Competence Center GmbH, Hagenberg, Austria;Escuela Superior de Informatica, Paseo de la Universidad, Ciudad Real, Spain;Escuela Superior de Informatica, Paseo de la Universidad, Ciudad Real, Spain;Escuela Superior de Informatica, Paseo de la Universidad, Ciudad Real, Spain

  • Venue:
  • Applied Artificial Intelligence
  • Year:
  • 2010

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Abstract

Rendering is the process of generating a 2D image from the abstract description of a 3D scene. In spite of the development of new techniques and algorithms, the computational requirements of photorealistic rendering are huge so that it is not possible to render them in real time. In addition, the adequate configuration of rendering quality parameters is very difficult to be done by inexpert users, and they are usually set higher than in fact are needed. This article presents an architecture called MAgArRO to optimize the rendering process in a distributed, noncentralized way through a multiagent solution, by making use of expert knowledge or previous jobs to reduce the final rendering. Experimental results prove that this novel approach offers a promising research line to optimize the rendering of photorealistic images.