Skip to main content

Control of Constraint Weights for a 2D Autonomous Camera

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5549))

Abstract

This paper addresses the problem of deducing and adjusting constraint weights at run time to guide the movement of the camera in an informed and controlled way in response to the requirements of the shot. This enables the control of weights at the frame level. We analyze the mathematical representation of the cost structure of the search domain so that the constraint solver can search the domain efficiently. Here we consider a simple tracking shot of a single target without occlusion or other environment elements. In this paper we consider only the distance, orientation, frame coherence distance and frame coherence rotation constraints in 2D. The cost structure for 2D suggests the use of a binary search to find the solution camera position.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Alam, M.S.: Control of Constraint Weights for an Autonomous Camera. Master’s Thesis, School of Computer Science, University of Windsor, Windsor, Canada (2008)

    Google Scholar 

  • Bares, W.H., McDermott, S., Boudreaux, C., Thainimit, S.: Virtual 3D camera composition from frame constraints. In: MULTIMEDIA 2000: Proceedings of the Eighth ACM International Conference on Multimedia, pp. 177–186. ACM Press, New York (2000a)

    Google Scholar 

  • Bares, W.H., Thainimit, S., McDermott, S.: A model for constraint-based camera planning. In: AAAI 2000 Spring Symposium Series on Smart Graphics, Stanford, California, USA, March 2000, pp. 84–91 (2000b)

    Google Scholar 

  • Bourne, O., Sattar, A.: Applying constraint satisfaction techniques to 3D camera control. In: Webb, G.I., Yu, X. (eds.) AI 2004. LNCS, vol. 3339, pp. 658–669. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  • Bourne, O., Sattar, A.: Applying constraint weighting to autonomous camera control. In: Artificial Intelligence and Interactive Digital Entertainment, Marina Del Ray, CA, USA, pp. 3–8. AAAI Press, Menlo Park (2005a)

    Google Scholar 

  • Bourne, O., Sattar, A.: Evolving behaviours for a real-time autonomous camera. In: Proceedings of the Second Australasian Conference on Interactive Entertainment, Sydney, Australia, pp. 27–33 (2005b) ISBN 0-9751533-2-3/05/11

    Google Scholar 

  • Bourne, O.: Constraint-Based Intelligent Camera Control for Interactive Digital Entertainment. PhD Thesis, Institute of Integrated and Intelligent Systems, Griffith University, Queensland, Australia (2006)

    Google Scholar 

  • Bourne, O., Sattar, A.: Autonomous camera control with constraint satisfaction methods. In: Robin, S. (ed.) AI Game Programming Wisdom, March 2006, vol. 3, pp. 173–187. Charles River Media (2006)

    Google Scholar 

  • Christie, M., Normand, J.-M.: A semantic space partitioning approach to virtual camera composition. In: Proceedings of the Annual Eurographics Conference, vol. 24, pp. 247–256 (2005)

    Google Scholar 

  • Halper, N., Helbing, R., Strothotte, T.: A camera engine for computer games: managing the trade-off between constraint satisfaction and frame coherence. In: Chalmers, A., Rhyne, T. (eds.) Proceedings of the Eurographics 2001 Conference, Manchester, UK, September 2001, vol. 20(3), pp. 174–183 (2001)

    Google Scholar 

  • Katz, S.: Film Directing Shot by Shot: Visualizing from Concept to Screen. Michael Wiese Productions, Studio City, CA 91604, USA (1991)

    Google Scholar 

  • Mascelli, J.: The Five C’s of Cinematography: Motion Picture Filming Techniques. Silman-James Press, USA (1998)

    Google Scholar 

  • Pickering, J.H.: Intelligent Camera Planning for Computer Graphics. PhD Thesis, Department of Computer Science, University of York (2002)

    Google Scholar 

  • Thompson, R.: Grammar of the Shot. Focal Press (1998) ISBN 0-240-51398-3

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Alam, M.S., Goodwin, S.D. (2009). Control of Constraint Weights for a 2D Autonomous Camera. In: Gao, Y., Japkowicz, N. (eds) Advances in Artificial Intelligence. Canadian AI 2009. Lecture Notes in Computer Science(), vol 5549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01818-3_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01818-3_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01817-6

  • Online ISBN: 978-3-642-01818-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics