Inverse Direct Lighting with a Monte Carlo Method and Declarative Modelling

  • Vincent Jolivet
  • Dimitri Plemenos
  • Patrick Poulingeas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2330)


In inverse lighting problems, a lot of optimization techniques have been used. A new method in the framework of radiosity is presented here, using a simple Monte-Carlo method to find the positions of the lights in a direct lighting. Declarative modelling will also be used to allow the designer to describe in a more intuitive way his lighting wishes. Declarative modelling will propose to the user several solutions, and probably some interesting scenes not previously imagined by the designer.


Direct Lighting Declarative Modelling Luminous Flow Lighting Patch Declarative Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. [1]
    M. Contensin M., J.-L. Maltret. Computer Aided Lighting for Architects and Designers. IKM’97, Weimar, Février 1997.Google Scholar
  2. [2]
    A.C. Costa, A.A. Sousa, F.N. Ferreira. Optimization and Lighting Design. WSCG’99.Google Scholar
  3. [3]
    A.C. Costa, A.A. Sousa, F.N. Ferreira. Lighting Design: a Goal based Approach using Optimization. 10th EG Workshop on Rendering, 1999.Google Scholar
  4. [4]
    E. Desmontils. Formulation des Propriétés en Modélisation Déclarative à l’Aide des Ensembles Flous. Rapport de Recherche IRIN —106. Décembre 1995.Google Scholar
  5. [5]
    J. Elorza, I. Rudomin. An Interactive System for Solving Inverse Illumination Problems using Genetic Algorithms. Computacion Visual 1997.Google Scholar
  6. [6]
    R.L. Graham. An Efficient Algorithm for Determining the Convex Hull of a Finite Set of Points in the Plane. Information Processing Letters, 1. 1972.Google Scholar
  7. [7]
    V. Harutunian, J.C. Morales, J.R. Howell. Radiation Exchange within an Enclosure of Diffuse-Gray Surfaces: The Inverse Problem. ASME/AIAA International Heat Transfer Conference, 1995.Google Scholar
  8. [8]
    J.K. Kawai, J.S. Painter, M.F. Cohen. Radioptimization — Goal Based Rendering. SIGGRAPH’93.Google Scholar
  9. [9]
    M. Oguma, J.R. Howell. Solution of the Two-Dimensional Blackbody Inverse Radiation Problem by Inverse Monte-Carlo Method. ASME/JSME Thermal Engineering Conference, 1995.Google Scholar
  10. [10]
    P. Poulin, A. Fournier. Lights from Highlights and Shadows. March 1992, Symposium on Interactive 3D Graphics.Google Scholar
  11. [11]
    D. Plemenos. Declarative Modelling by Hierarchical Decomposition.The Actual State of the MultiFormes Project. GraphiCon’95, St Petersbourg, 1-5 juillet 1995.Google Scholar
  12. [12]
    P. Poulingeas. L’Eclairage Inverse-Etat de l’Art. Rapport de Recherche MSI 01-01. Octobre 2001.Google Scholar
  13. [13]
    G. Patow, X. Pueyo. A Survey on Inverse Reflector Design and Light Source Distribution Problems. Institut d’Informàtica i Aplicacions, Universitat de Girona. Private Communication.Google Scholar
  14. [14]
    G. Patow, X. Pueyo. A Survey on Inverse Emittance and Inverse Reflectometry Computation Problems. Institut d’Informàtica i Aplicacions, Universitat de Girona. Private Communication.Google Scholar
  15. [15]
    P. Poulin, K. Ratib, M. Jacques. Sketching Shadows and Highlights to position Lights. Proceedings of Computer Graphics International 1997.Google Scholar
  16. [16]
    C. Schoeneman, J. Dorsey, B. Smits, J. Arvo, D. Greenberg. Painting with Light. SIGGRAPH’93.Google Scholar
  17. [17]
    P. Shirley. Radiosity via Ray Tracing. Graphics Gems II, p. 306–310, James Arvo Ed., Academic Press, San Diego. 1991Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Vincent Jolivet
    • 1
  • Dimitri Plemenos
    • 1
  • Patrick Poulingeas
    • 1
  1. 1.Laboratoire MSILimogesFrance

Personalised recommendations