Fast rendering of large crowds using GPU

Hunki Park, Junghyun Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

This paper proposes a fast rendering algorithm for real-time animation of large crowds, which is essential for video games with a large number of non-player characters. The proposed approach leaves the minimal work of rendering to CPU, and makes GPU take all the major work, including LOD assignment and view frustum culling, which have been the typical tasks of CPU. By offloading the rendering overhead from CPU, the approach enables the CPU to perform intensive computations for crowd simulation. The experiments show that tens of thousands of characters can be skin-animated in real time.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages197-202
Number of pages6
Volume5309 LNCS
DOIs
Publication statusPublished - 2008 Dec 15
Event7th International Conference on Entertainment Computing, ICEC 2008 - Pittsburgh, PA, United States
Duration: 2008 Sep 252008 Sep 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5309 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Entertainment Computing, ICEC 2008
CountryUnited States
CityPittsburgh, PA
Period08/9/2508/9/27

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Keywords

  • Crowd rendering
  • GPU
  • Instancing
  • Skinning

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Park, H., & Han, J. (2008). Fast rendering of large crowds using GPU. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5309 LNCS, pp. 197-202). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5309 LNCS). https://doi.org/10.1007/978-3-540-89222-9-24