skip to main content
10.1145/1450579.1450596acmconferencesArticle/Chapter ViewAbstractPublication PagesvrstConference Proceedingsconference-collections
research-article

GPU techniques for creating visually diverse crowds in real-time

Published:27 October 2008Publication History

ABSTRACT

Real-time crowds significantly improve the realism of virtual environments, therefore their use has increased considerably over the last few years in a variety of applications, including real-time games and virtual tourism. However, due to current hardware limitations, crowd variety tends to be sacrificed in order for the crowd simulation to execute in real-time, which decreases the quality and realism of the crowd.

Currently the little variety that is incorporated in real-time crowds tends to be applied by modulating each avatar with random colours, which has a detrimental effect on the texture quality. Furthermore, the existing crowd variety is often hard to define and control. To overcome these problems a set of techniques are presented, which defines and controls crowd variety, to further improve on current variety and quality of crowds. These techniques permit variety to be introduced: by changing the body mass via the application of a displacement map onto the mesh; by scaling the skeleton of the avatar; by applying HSV colour shifts to different parts of the avatar; and by transferring textures between avatar models. The appearance of the avatars under animation is also improved via the use of muscle displacement within the mesh. With the new techniques, the visual quality of the crowd is improved due to the increase in diversity.

Skip Supplemental Material Section

Supplemental Material

file173-3.wmv

wmv

41.8 MB

References

  1. Allen, B., Curless, B., and Popovic, Z. 2004. Exploring the space of human body shapes: data-driven synthesis under anthropometric control. SAE TRANSACTIONS 113.Google ScholarGoogle Scholar
  2. Blanz, V., and Vetter, T. 1999. A morphable model for the synthesis of 3d faces. In International Conference on Computer Graphics and Interactive Techniques, 187--194. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. DeCarlo, D., Metaxas, D., and Stone, M. 1998. An anthropometric face model using variational techniques. In SIGGRAPH '98: Proceedings of the 25th annual conference on Computer graphics and interactive techniques, ACM, 67--74. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Dobbyn, S., Hamill, J., O'Conor, K., and O'Sullivan, C. 2005. Geopostors: a real-time geometry / impostor crowd rendering system. In I3D '05: Proceedings of the 2005 symposium on Interactive 3D graphics and games, ACM, New York, NY, USA, 95--102. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Dudash, B. 2007. Skinned instancing. In NVIDIA Direct3D SDK 10 Code Samples.Google ScholarGoogle Scholar
  6. Kasap, M., and Magnenat-Thalmann, N. 2007. Parameterized human body model for real-time applications. In Cyber-world, IEEE Computer Society, Hannover, Germany, 160--167. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Kraevoy, V., and Sheffer, A. 2004. Cross-parameterization and compatible remeshing of 3d models. ACM TRANSACTIONS ON GRAPHICS 23, 3, 858--866. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Lee, W.-S., and Magnenat-Thalmann, N. 2001. Virtual body morphing. In Computer Animation, 2001. The Fourteenth Conference on Computer Animation, 158--166.Google ScholarGoogle Scholar
  9. McDonnell, R., Larkin, M., Dobbyn, S., Collins, S., and O'Sullivan, S. 2008. Clone attack! perception of crowd variety. In ACM Transactions on Graphics 27(3), 2008, ACM, New York, NY, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Seo, H., Yahia-Cherif, L., Goto, T., and Magnenat-Thalmann, N. 2002. Genesis: Generation of e-population based on statistical information. In Computer Animation, 81--85. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Seo, H., Cordier, F., and Magnenat-Thalmann, N. 2003. Synthesizing animatable body models with parameterized shape modifications. In SCA '03: Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation, Eurographics Association, San Diego, California, 120--125. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Tecchia, F., Loscos, C., and Chrysanthou, Y. 2002. Image-based crowd rendering. IEEE Comput. Graph. Appl. 22, 2, 36--43. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ulicny, B., de Heras Ciechomski, P., and Thalmann, D. 2005. Crowdbrush: interactive authoring of real-time crowd scenes. In SIGGRAPH '05: ACM SIGGRAPH 2005 Courses, ACM, New York, NY, USA, 3. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. GPU techniques for creating visually diverse crowds in real-time

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        VRST '08: Proceedings of the 2008 ACM symposium on Virtual reality software and technology
        October 2008
        288 pages
        ISBN:9781595939517
        DOI:10.1145/1450579

        Copyright © 2008 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 October 2008

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        VRST '08 Paper Acceptance Rate12of68submissions,18%Overall Acceptance Rate66of254submissions,26%

        Upcoming Conference

        VRST '24

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader