This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Illumination from Shadows
March 2003 (vol. 25 no. 3)
pp. 290-300

Abstract—In this paper, we introduce a method for recovering an illumination distribution of a scene from image brightness inside shadows cast by an object of known shape in the scene. In a natural illumination condition, a scene includes both direct and indirect illumination distributed in a complex way, and it is often difficult to recover an illumination distribution from image brightness observed on an object surface. The main reason for this difficulty is that there is usually not adequate variation in the image brightness observed on the object surface to reflect the subtle characteristics of the entire illumination. In this study, we demonstrate the effectiveness of using occluding information of incoming light in estimating an illumination distribution of a scene. Shadows in a real scene are caused by the occlusion of incoming light and, thus, analyzing the relationships between the image brightness and the occlusions of incoming light enables us to reliably estimate an illumination distribution of a scene even in a complex illumination environment. This study further concerns the following two issues that need to be addressed. First, the method combines the illumination analysis with an estimation of the reflectance properties of a shadow surface. This makes the method applicable to the case where reflectance properties of a surface are not known a priori and enlarges the variety of images applicable to the method. Second, we introduce an adaptive sampling framework for efficient estimation of illumination distribution. Using this framework, we are able to avoid a unnecessarily dense sampling of the illumination and can estimate the entire illumination distribution more efficiently with a smaller number of sampling directions of the illumination distribution. To demonstrate the effectiveness of the proposed method, we have successfully tested the proposed method by using sets of real images taken in natural illumination conditions with different surface materials of shadow regions.

[1] R. Baribeau, M. Rioux, and G. Godin, “Color Reflectance Modeling Using a Polychromatic Laser Range Sensor,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 263-269, Feb. 1992.
[2] R. Basri and D. Jacobs, “Lambertian Reflectance and Linear Subspaces,” Proc. IEEE Int'l Conf. Computer Vision’01, pp. 383-389, 2001.
[3] J. Bouguet and P. Perona, “3D Photography on Your Desk,” Proc. IEEE Int'l Conf. Computer Vision’98, pp. 43-50, 1998.
[4] M.F. Cohen, D.P. Greenberg, D.S. Immel, and P.J. Brock, “An Efficient Radiosity Approach for Realistic Image Synthesis,” IEEE Computer Graphics&Applications, vol. 6, no. 3, pp. 26-35, Mar. 1986.
[5] D.A. Forsyth and J. Ponce, Computer Vision: A Modern Approach. Prentice Hall, 2002.
[6] A. Fournier, A. Gunawan, and C. Romanzin, “Common Illumination between Real and Computer Generated Scenes,” Proc. Graphics Interface’93, pp. 254-262, 1993.
[7] G.E. Healey, S.A. Shafer, and L.B. Wolff, Physics-Based Vision Principles and Practice, Color. Boston: Jones and Bartlett, 1992.
[8] B.K.P. Horn, “Understanding Image Intensities,” Artificial Intelligence, vol. 8, no. 2, pp. 201-231, 1977.
[9] B.K. Horn, Robot Vision. Cambridge, Mass.: MIT Press, 1986.
[10] B.K.P. Horn, “Obtaining Shape from Shading Information,” The Psychology of Computer Vision, New York: McGraw-Hill, 1975.
[11] B.K.P. Horn and M.J. Brooks, “The Variational Approach to Shape from Shading,” Computer Vision, Graphics, and Image Processing, vol. 33. no. 2, pp. 174-208, 1986.
[12] K. Ikeuchi and B.K.P. Horn, “Numerical Shape from Shading and Occluding Boundaries,” Artificial Intelligence, vol. 17, nos. 1-3, pp. 141-184, 1981.
[13] K. Ikeuchi and K. Sato, “Determining Reflectance Using Range and Brightness Images,” Proc. IEEE Int'l Conf. Computer Vision’90, pp. 12-20, 1990.
[14] J.K. Kawai, J.S. Painter, and M.F. Cohen, "Radioptimization—Goal Based Rendering," Proc. Computer Graphics Ann. Conf. Series (SIGGRAPH '93), pp. 147-154, Aug. 1993.
[15] G. Kay and T. Caelli, “Estimating the Parameters of an Illumination Model Using Photometric Stereo,” Graphical Models and Image Processing, vol. 57, no. 5, pp. 365-388, 1995.
[16] J.R. Kender and E.M. Smith, “Shape from Darkness: Deriving Surface Information from Dynamic Shadows,” Proc. IEEE Int'l Conf. Computer Vision’87, pp. 539-546, 1987.
[17] T. Kim, Y. Seo, and K. Hong, “Improving AR Using Shadows Arising from Natural Illumination Distribution in Video Sequence,” Proc. IEEE Int'l Conf. Computer Vision’01, pp. 329-334, July 2001.
[18] J. Lu and J. Little, “Reflectance Function Estimation and Shape Recovery from Image Sequence of a Rotating Object,” Proc. IEEE Int'l Conf. Computer Vision’95, pp. 80-86, 1995.
[19] A.K. Mackworth, “On the Interpretation of Drawings as Three-Dimensional Scenes,” doctorial dissertation, Univ. of Sussex, 1974.
[20] S.R. Marschner and D.P. Greenberg, “Inverse Lighting for Photography,” Proc. IS&T/SID Fifth Color Imaging Conf., pp. 262-265, 1997.
[21] P. Moon and D.E. Spencer, The Photic Field. Cambridge, Mass.: The MIT Press, 1981.
[22] S.K. Nayar, K. Ikeuchi, and T. Kanade, "Surface Reflection: Physical and Geometrical Perspectives," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 7, pp. 611-634, 1991.
[23] K. Nishino, Z. Zhang, and K. Ikeuchi, “Determining Reflectance Parameters and Illumination Distribution from Sparse Set of Images for View-Dependent Image Synthesis,” Proc. IEEE Int'l Conf. Computer Vision’01, pp. 599-606, July 2001.
[24] A.P. Pentland, “Linear Shape From Shading,” Int'l J. Computer Vision, vol. 4, no. 2, pp. 153-162, 1990.
[25] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling, Numerical Recipes in C.Cambridge, England: Cambridge Univ. Press, 1988.
[26] R. Ramamoorthi and P. Hanrahan, “A Signal-Procession Framework for Inverse Rendering,” Proc. ACM SIGGRAPH’01, pp. 117-128, Aug. 2001.
[27] I. Sato, Y. Sato, and K. Ikeuchi, Illumination Distribution from Shadows Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 306-312, 1999.
[28] I. Sato, Y. Sato, and K. Ikeuchi, “Illumination Distribution from Brightness in Shadows: Adaptive Estimation of Illumination Distribution with Unknown Reflectance Properties in Shadow Regions,” Proc. Int'l Conf. Computer Vision, pp. 875-883, 1999.
[29] I. Sato, Y. Sato, and K. Ikeuchi, “Acquiring a Radiance Distribution to Superimpose Virtual Objects onto a Real Scene,” IEEE Trans. Visualization and Computer Graphics, vol. 5, no. 1, pp. 1-12, 1999.
[30] Y. Sato, M.D. Wheeler, and K. Ikeuchi, “Object Shape and Reflectance Modeling from Observation,” Proc. SIGGRAPH '97, pp. 379-387, 1997.
[31] C. Schoeneman, J. Dorsey, B. Smits, J. Arvo, and D. Greenburg, “Painting with Light,” Proc. ACM SIGGRAPH’93, pp. 143-146, 1993.
[32] S.A. Shafer and T. Kanade, “Using Shadows in Finding Surface Orientations,” Computer Vision, Graphics, and Image Processing, vol. 22, no. 1, pp. 145-176, 1983.
[33] S. Tominaga and N. Tanaka, “Estimating Reflectance Parameters from a Single Color Image,” IEEE Computer Graphics&Applications, vol. 20, no. 5, pp. 58-66, 2000.
[34] K.E. Torrance and E.M. Sparrow, “Theory for Off-Specular Reflection from Roughened Surface,” J. Optical Soc. Am., vol. 57, pp. 1105-1114, 1967.
[35] Y. Yu, P. Debevec, J. Malik, and T. Hawkins, “Inverse Global Illumination: Recovering Reflectance Models of Real Scenes from Photographs,” Proc. SIGGRAPH '99, pp. 215-224, July 1998.
[36] Y. Zhang and Y.-H. Yang, Illuminant Direction Determination for Multiple Light Sources Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 269-276, 2000.
[37] 3D Construction Company,http:/www.3dcomstruction.com. 2000.

Index Terms:
Computer vision, physics-based vision, illumination distribution estimation.
Citation:
Imari Sato, Yoichi Sato, Katsushi Ikeuchi, "Illumination from Shadows," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 3, pp. 290-300, March 2003, doi:10.1109/TPAMI.2003.1182093
Usage of this product signifies your acceptance of the Terms of Use.