Skip to main content
SpringerLink
Log in

Simulating Human Activities for Synthetic Inputs to Sensor Systems

  • Chapter
Distributed Video Sensor Networks

Abstract

We are developing human activity simulations that could be used to test distributed video sensor networks. Our ultimate goals are to build statistical models of pedestrian density and flows at a number of urban locations and to correlate those flows with population movement and density models represented in a spatiotemporal modeling system. In order to create known populace flows, we have built a virtual populace simulation system, called CAROSA, which permits the authoring of functional crowds of people going about role-, context-, and schedule-dependent activities. The capabilities and authoring tools for these functional crowd simulations are described with the intention of readily creating ground truth data for distributed sensor system design and evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Work is in progress to extend this scheme to large exterior environments; the modeling principles remain the same.

References

  1. Allbeck, J., Kipper, K., Adams, C., Schuler, W., Zoubanova, E., Badler, N., Palmer, M., Joshi, A.: ACUMEN: Amplifying control and understanding of multiple entities. In: Autonomous Agents and Multi-Agent Systems, pp. 191–198 (2002)

    Google Scholar 

  2. Bindiganavale, R.: Building parameterized action representations from observation. Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA (2000)

    Google Scholar 

  3. Brockington, M.: Level-of-detail AI for a large role-playing game. In: Rabin, S. (ed.) AI Game Programming Wisdom, pp. 419–425. Charles River Media, Inc., Hingham (2002)

    Google Scholar 

  4. Brogan, D., Hodgins, J.: Group behaviors for systems with significant dynamics. Auton. Robots 4, 137–153

    Google Scholar 

  5. CAL3D. 3D Character Animation Library: http://home.gna.org/cal3d/, Last visited May 2009

  6. Chenney, S.: Flow tiles. In: ACM SIGGRAPH/ Eurographics Proceedings of Symposium on Computer Animation, pp. 233–242 (2004)

    Google Scholar 

  7. DePaiva, D.C., Vieira, R., Musse, S.R.: Ontology-based crowd simulation for normal life situations. In: Proceedings of Computer Graphics International, Stony Brook, NY, 2005, pp. 221–226. IEEE, New York (2005)

    Google Scholar 

  8. GeniusConnect: GeniusConnect. http://www.geniusconnect.com/articles/Products/2/3/, Last visited May 2009

  9. Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407, 487–490

    Google Scholar 

  10. Isbister, K., Hayes-Roth, B.: Social implications of using synthetic characters: an examination of a role-specific intelligent agent. Knowledge Systems Laboratory, Stanford University, Stanford, CA (1998)

    Google Scholar 

  11. Kallmann, M., Thalmann, D.: Direct 3D Interaction with smart objects. In: Proceedings of the ACM Symposium on Virtual Reality Software and Technology, London, United Kingdom, 1999, pp. 124–130. ACM, New York (1999)

    Google Scholar 

  12. Lee, K.H., Choi, M.G., Hong, Q., Lee, J.: Group behavior from video: A data-driven approach to crowd simulation. In: ACM SIGGRAPH/Eurographics Symposium on Computer Animation, San Diego, 2007, pp. 109–118 (2007)

    Google Scholar 

  13. Lerner, A., Fitusi, E., Chrysanthou, Y., Cohen-Or, D.: Fitting behaviors to pedestrian simulations. In: Symposium on Computer Animation, New Orleans, LA, 2009, pp. 199–208. ACM, New York (2009)

    Google Scholar 

  14. Ma, Y., Cisar, P., Kembhavi, A.: Motion segmentation and activity representation in crowds. Int. J. Imaging Syst. Technol. 19(2), 80–90

    Google Scholar 

  15. MASSIVE_SOFTWARE_Inc.: 3D animation system for crowd-related visual effects, http://www.massivesoftware.com, Last visited Oct. 2009

  16. McDonnell, R., Micheal, L., Hernandez, B., Rudomin, I., O’Sullivan, C.: Eye-catching crowds: saliency based selective variation. In: ACM SIGGRAPH, New Orleans, Louisiana, 2009, pp. 1–10. ACM, New York (2009)

    Google Scholar 

  17. O’Sullivan, C., Cassell, J., Vilhjalmsson, H., Dobbyn, S., Peters, C., Leeson, W., Giang, T., Dingliana, J.: Crowd and group simulation with levels of detail for geometry, motion and behavior. In: Third Irish Workshop on Computer Graphics (2002)

    Google Scholar 

  18. Orge: http://www.ogre3d.org/, Last visited January 2010

  19. Parkes, D., Thrift, N.: Times, Space, and Places: A Chronogeographic Perspective. Wiley, Chichester (1980)

    Google Scholar 

  20. Pelechano, N., Allbeck, J., Badler, N.: Virtual Crowds: Methods, Simulation, and Control. Morgan and Claypool Publishers, San Rafael (2008)

    Google Scholar 

  21. Pelechano, N., Allbeck, J.M., Badler, N.I.: Controlling individual agents in high-density crowd simulation. In: ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA, San Diego, CA, 2007. ACM Press, New York (2007)

    Google Scholar 

  22. Pelechano, N., Badler, N.: Modeling crowd and trained leader behavior during building evacuation. IEEE Comput. Graph. Appl. 26(6), 80–86

    Google Scholar 

  23. Prendinger, H., Ishizuka, M.: Social role awareness in animated agents. In: 5th International Conference on Autonomous Agents, pp. 270–277. ACM Press, New York (2001)

    Google Scholar 

  24. Reynolds, C.: Flocks, herds, and schools: A distributed behavior model. In: Proceedings of ACM SIGGRAPH, pp. 25–34 (1987)

    Google Scholar 

  25. Shao, W., Terzopoulos, D.: Autonomous pedestrians. In: Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation (Los Angeles, California, 2005), pp. 19–28. ACM Press, New York (2005)

    Chapter  Google Scholar 

  26. Sung, M., Gleicher, M., Chenney, S.: Scalable behaviors for crowd simulation. Comput. Graph. Forum 23(3), 519–528

    Google Scholar 

  27. Thalmann, D., Musse, S.R.: Crowd Simulation. Springer, Berlin (2007)

    Google Scholar 

  28. Thalmann, D., Musse, S.R., Kallmann, M.: Virtual humans’ behavior: individuals, groups, and crowds. In: Proceedings of Digital Media Futures, pp. 13–15 (1999)

    Google Scholar 

  29. Wright, W.: The Sims. Electronic Arts, 1st edn. (2000)

    Google Scholar 

  30. Ya-Dong, W., Jian-Kang, W., Ashraf, A.K., Wei-Min, H.: Tracking a variable number of human groups in video using probability hypothesis density. In: Proceedings of the 18th International Conference on Pattern Recognition, vol. 03. IEEE Computer Society, Los Alamitos (2006)

    Google Scholar 

  31. Yeh, H., Curtis, S., Patil, S., van den Berg, J., Manocha, D., Lin, M.: Composite agents. In: Proceedings of Symposium on Computer Animation, Dublin, Ireland, 2008. Eurographics Association, Zurich (2008)

    Google Scholar 

  32. Yu, Q., Terzopoulos, D.: A decision network framework for the behavioral animation of virtual humans. In: Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, San Diego, California, 2007, pp. 119–128. Eurographics Association, Zurich (2007)

    Google Scholar 

Download references

Acknowledgements

Partial support for this effort is gratefully acknowledged from the U.S. Army “SUBTLE” MURI, a Lockheed-Martin Corporation Strategic Technology Thread Grant, and George Mason University. We also appreciate donations from Autodesk and nVidia. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors.

Author information

Authors and Affiliations

    Authors
    1. Jan M. Allbeck
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. Norman I. Badler
      View author publications

      You can also search for this author in PubMed Google Scholar

    Corresponding author

    Correspondence to Jan M. Allbeck .

    Editor information

    Editors and Affiliations

    1. Center for Research, Intelligent Systems, University of California, Riverside, Riverside, 92521, California, USA

      Bir Bhanu

    2. Dept. Computer Science & Engineering, University of California, Riverside, Riverside, 92521, California, USA

      Chinya V. Ravishankar

    3. Dept. Electrical Engineering, University of California, Riverside, Riverside, 92521, California, USA

      Amit K. Roy-Chowdhury

    4. Dept. Electrical Engineering, Packard Bldg., Stanford University, Serra Mall 350, Stanford, 94305-9505, California, USA

      Hamid Aghajan

    5. Dept. Computer Science, University of California, Los Angeles, Boelter Hall 4731, Los Angeles, 90095-1596, California, USA

      Demetri Terzopoulos

    Rights and permissions

    Reprints and permissions

    Copyright information

    © 2011 Springer-Verlag London Limited

    About this chapter

    Cite this chapter

    Allbeck, J.M., Badler, N.I. (2011). Simulating Human Activities for Synthetic Inputs to Sensor Systems. In: Bhanu, B., Ravishankar, C., Roy-Chowdhury, A., Aghajan, H., Terzopoulos, D. (eds) Distributed Video Sensor Networks. Springer, London. https://doi.org/10.1007/978-0-85729-127-1_13

    Download citation

    • DOI: https://doi.org/10.1007/978-0-85729-127-1_13

    • Publisher Name: Springer, London

    • Print ISBN: 978-0-85729-126-4

    • Online ISBN: 978-0-85729-127-1

    • eBook Packages: Computer ScienceComputer Science (R0)

    Publish with us

    Policies and ethics

    Search

    Navigation