Advanced Composition in Virtual Camera Control

  • Rafid Abdullah
  • Marc Christie
  • Guy Schofield
  • Christophe Lino
  • Patrick Olivier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6815)

Abstract

Rapid increase in the quality of 3D content coupled with the evolution of hardware rendering techniques urges the development of camera control systems that enable the application of aesthetic rules and conventions from visual media such as film and television. One of the most important problems in cinematography is that of composition, the precise placement of elements in shot. Researchers already considered this problem, but mainly focused on basic compositional properties like size and framing. In this paper, we present a camera system that automatically configures the camera in order to satisfy advanced compositional rules. We have selected a number of those rules and specified rating functions for them, then using optimisation we find the best possible camera configuration. Finally, for better results, we use image processing methods to rate the satisfaction of rules in shot.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Banerjee, S., Evans, B.L.: Unsupervised automation of photographic composition rules in digital still cameras. In: Proceedings of SPIE Conference on Sensors, Color, Cameras, and Systems for Digital Photography, vol. 5301, pp. 364–373 (2004)Google Scholar
  2. 2.
    Bares, W.: A photographic composition assistant for intelligent virtual 3d camera systems. In: Butz, A., Fisher, B., Krüger, A., Olivier, P. (eds.) SG 2006. LNCS, vol. 4073, pp. 172–183. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Bares, W., McDermott, S., Boudreaux, C., Thainimit, S.: Virtual 3D Camera Composition from Frame Constraints. In: Proceedings of the Eighth ACM International Conference on Multimedia, pp. 177–186. ACM, New York (2000)CrossRefGoogle Scholar
  4. 4.
    Burelli, P., Di Gaspero, L., Ermetici, A., Ranon, R.: Virtual camera composition with particle swarm optimization. In: Butz, A., Fisher, B., Krüger, A., Olivier, P., Christie, M. (eds.) SG 2008. LNCS, vol. 5166, pp. 130–141. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Byers, Z., Dixon, M., Smart, W.D., Grimm, C.M.: Say Cheese! Experiences with a Robot Photographer. AI Magazine 25(3) 37 (2004)Google Scholar
  6. 6.
    Carlisle, A., Dozier, G.: An off-the-shelf pso. In: Proceedings of the Workshop on Particle Swarm Optimization, vol. 1, pp. 1–6 (2001)Google Scholar
  7. 7.
    Giors, J.: The full spectrum warrior camera system (2004)Google Scholar
  8. 8.
    Gooch, B., Reinhard, E., Moulding, C., Shirley, P.: Artistic composition for image creation. In: Eurographics Workshop on Rendering, pp. 83–88 (2001)Google Scholar
  9. 9.
    Grill, T., Scanlon, M.: Photographic Composition. Amphoto Books (1990)Google Scholar
  10. 10.
    Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)Google Scholar
  11. 11.
    Lino, C., Christie, M., Lamarche, F., Schofield, G., Olivier, P.: A Real-time Cinematography System for Interactive 3D Environments. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA) (July 2010)Google Scholar
  12. 12.
    Liu, L., Chen, R., Wolf, L., Cohen-Or, D.: Optimizing photo composition. Computer Graphic Forum (Proceedings of Eurographics) 29(2), 469–478 (2010)CrossRefGoogle Scholar
  13. 13.
    Lok, S., Feiner, S., Ngai, G.: Evaluation of Visual Balance for Automated Layout. In: Proceedings of the 9th International Conference on Intelligent User Interfaces, pp. 101–108. ACM, New York (2004)Google Scholar
  14. 14.
    Olivier, P., Halper, N., Pickering, J., Luna, P.: Visual composition as optimisation. In: AISB Symposium on AI and Creativity in Entertainment and Visual Art, pp. 22–30 (1999)Google Scholar
  15. 15.
    Pedersen, M.E.H.: Tuning & Simplifying Heuristical Optimization (PhD Thesis). sl: School of Engineering Sciences. Ph.D. thesis, University of Southampton, United Kingdom (2010)Google Scholar
  16. 16.
    Ranon, R., Christie, M., Urli, T.: Accurately measuring the satisfaction of visual properties in virtual camera control. In: Taylor, R., Boulanger, P., Krger, A., Olivier, P. (eds.) Smart Graphics. LNCS, vol. 6133, pp. 91–102. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    Ward, P.: Picture Composition for Film and Television. Focal Press (2003)Google Scholar
  18. 18.
    Weisstein, E.W.: Least squares fitting–perpendicular offsets (2010), http://mathworld.wolfram.com/LeastSquaresFittingPerpendicularOffsets.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rafid Abdullah
    • 1
  • Marc Christie
    • 2
  • Guy Schofield
    • 1
  • Christophe Lino
    • 2
  • Patrick Olivier
    • 1
  1. 1.School of Computing ScienceNewcastle UniversityUK
  2. 2.INRIA Rennes - Bretagne AtlantiqueFrance

Personalised recommendations