Abstract
The image irradiance of a three-dimensional object is known to be the function of three components: the distribution of light sources, the shape, and reflectance of a real object surface. In the past, recovering the shape and reflectance of an object surface from the recorded image brightness has been intensively investigated. On the other hand, there has been little progress in recovering illumination from the knowledge of the shape and reflectance of a real object. In this paper, we propose a new method for estimating the illumination distribution of a real scene from image brightness observed on a real object surface in that scene. More specifically, we recover the illumination distribution of the scene from a radiance distribution inside shadows cast by an object of known shape onto another object surface of known shape and reflectance. By using the occlusion information of the incoming light, we are able to reliably estimate the illumination distribution of a real scene, even in a complex illumination environment.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
R. Baribeau, M. Rioux, and G. Godin, “Color Reflectance Modeling Using a Polychromatic Laser Range Sensor” IEEE Trans. PAMI, vol. 14, no. 2, pp. 263–269, 1992.
J. Bouguet and P. Perona, “3D Photography on Your Desk,” Intl. Conference on Computer Vision, pp.43–50, 1998.
P. E. Debevec, “Rendering Synthetic Objects into Real Scenes: Bridging Traditional and Image-based Graphics with Global Illumination and High Dynamic Range Photography,” Proc. SIGGRAPH 98, pp. 189–198, July, 1998.
G. Drettakis, L. Robert, S. Bougnoux, “Interactive Common Illumination for Computer Augmented Reality” Proc. 8th Eurographics Workshop on Rendering, pp. 45–57, 1997.
A. Fournier, A. Gunawan and C. Romanzin, “Common Illumination between Real and Computer Generated Scenes,”Proc. Graphics Interface ‘93, pp.254–262, 1993.
B. K. P. Horn, Robot Vision, The MIT Press, Cambridge, MA., 1986.
B. K. P. Horn, “Obtaining Shape from Shading Information,” Chapter 4 in The psychlogy of Computer Vision, McGraw-Hill Book Co., New York, N.Y, 1975.
B. K. P. Horn and M. J. Brooks, “The Variational Approach to Shape from Shading,” Computer Vision, Graphics, and Image Processing, 33(2), pp. 174–208, 1986.
K. Ikeuchi and B. K. P. Horn, “Numerical Shape from Shading and Occluding Boundaries,” Artificial Intelligence 17(1–3), pp.141–184, 1981.
K. Ikeuchi and T. Kanade, “Automatic Generation of Object Recognition Programs,” Proc. IEEE(76), No. 8, pp.1016–1035, 1988.
J. R. Kender and E. M. Smith, “Shape from Darkness: Deriving Surface Information from Dynamic Shadows,” Proc. Intl. Conference on Computer Vision, pp.539–546, 1987.
G. Kay and T. Caelli, “Estimating the Parameters of an Illumination Model using Photometric Stereo, “Graphial Models and Image Processing, vol. 57, no. 5, pp. 365–388, 1995.
J. Lu and J. Little, “Reflectance Function Estimation and Shape Recovery from Image Sequence of a Rotating Object, “Proc. IEEE Intl. Conference on Computer Vision ‘95, pp. 80–86, 1995.
A. K. Markworth, “On the Interpretation of Drawings as Three-Dimensional Scenes, “ PhD thesis, University of Sussex, 1974.
S. K. Nayar, K. Ikeuchi, and T. Kanade, “Surface reflection: physical and geometrical perspectives,” IEEE Trans. PAMI, vol. 13, no. 7, pp. 611–634, 1991.
A. P. Pentland, “Linear Shape From Shading,” Intl. J. Computer Vision, 4(2), ppl53–162, 1990.
W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, Cambridge, 1988.
Y. Sato, M. D. Wheeler, and K. Ikeuchi, “Object shape and reflectance modeling from observation,” Proc. SIGGRAPH 97, pp. 379–387, 1997.
S. A. Shafer and T. Kanade, “Using Shadows in Finding Surface Orientations,” Computer Vision, Graphics, and Image Processing, 22(1), pp. 145–176, 1983.
K. E. Torrance and E. M. Sparrow, “Theory for off-specular reflection from roughened surface,” J. Optical Society of America, vol.57, pp.1105–1114, 1967.
R. Tsai, “A Versatile Camera Calibration Technique for High Accuracy Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses,” IEEE J. Robotics and Automation, vol. 3, no. 4, pp. 323–344, 1987.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media New York
About this chapter
Cite this chapter
Sato, I., Sato, Y., Ikeuchi, K. (2001). Illumination Distribution from Shadows. In: Ikeuchi, K., Sato, Y. (eds) Modeling from Reality. The Springer International Series in Engineering and Computer Science, vol 640. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0797-0_7
Download citation
DOI: https://doi.org/10.1007/978-1-4615-0797-0_7
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5244-0
Online ISBN: 978-1-4615-0797-0
eBook Packages: Springer Book Archive