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Multiple Light Source Detection
April 2004 (vol. 26 no. 4)
pp. 509-514

Abstract—This paper presents the V2R algorithm, a novel method for multiple light source detection using a Lambertian sphere as a calibration object. The algorithm segments the image of the sphere into regions that are each illuminated by a single virtual light and subtracts the virtual lights of adjacent regions to estimate the light source vectors. The algorithm uses all pixels within a region to form a robust estimate of the corresponding virtual light. The circumstances under which the light source detection problem lacks a unique solution are discussed in detail and the way in which the V2R algorithm resolves the ambiguity is explained. The V2R algorithm includes novel procedures for identifying the critical lines that bound the regions, for estimating the light source vectors, and for identifying opposite light pairs. Experiments are performed on synthetic and real images and the performance of the V2R algorithm is compared to that of a recent algorithm from the literature. The experimental results demonstrate that the proposed algorithm is robust and that it gives substantially improved accuracy.

[1] A.P. Pentland, Finding the Illuminant Direction J. Optical Soc. of Am., vol. 72, pp. 448-455, 1982.
[2] W. Chojnacki, M.J. Brooks, and D. Gibbins, Revisiting Pentlands Estimator of Light-Source Direction J. Optical Soc. of Am. A Optics Image Science and Vision, vol. 11, no. 1, pp. 118-124, Jan. 1994.
[3] Q. Zheng and R. Chellappa, Estimation of Illuminant Direction, Albedo, and Shape from Shading IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 7, pp. 680-702, July 1991.
[4] 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.
[5] P.E. Debevec, Rendering Synthetic Objects into Real Scenes: Bridge Traditional and Image-Based Graphics with Global Illumination and High Dynamic Range Photography Proc. SIGGRAPH '98 Conf., pp. 189-198, July 1998.
[6] M.W. Powell, S. Sarkar, and D. Goldgof, A Simple Strategy for Calibrating the Geometry of Light Sources IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 9, pp. 1022-1027, Sept. 2001.
[7] Y. Yang and A. Yuille, Sources From Shading Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 534-539, 1991.
[8] D.H. Hougen and N. Ahuja, Estimation of the Light Source Distribution and Its Use in Integrated Shape Recovery from Stereo and Shading Proc. IEEE Fourth Int'l Conf. Computer Vision, pp. 148-155, May 1993.
[9] Y.-H. Yang, An Experimental Study of Light Source Determination for Computer Graphics Vision Interface, pp. 271-278, 1998.
[10] 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.
[11] Y. Zhang and Y.-H. Yang, Multiple Illuminant Direction Detection with Application to Image Synthesis IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 8, pp. 915-920, Aug. 2001.
[12] B.K.P. Horn, Robot Vision. The MIT Electrical Eng. and Computer Science Series, The MIT Press, 1986.
[13] S.R. Marschner and D.P. Greenberg, Inverse Lighting for Photography Proc. Fifth Color Imaging Conf., 1997.
[14] R. Ramamoorthi and P. Hanrahan, On the Relationship between Radiance and Irradiance: Determining the Illumination from Images of a Convex Lambertian Object J. Optical Soc. of Am., vol. 18, no. 10, pp. 2448-2459, 2001.
[15] R. Basri and D.W. Jacobs, Lambertian Reflectance and Linear Subspaces IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 2, pp. 218-233, Feb. 2003.
[16] Y. Wang and D. Samaras, Estimation of Multiple Illuminants from a Single Image of Arbitrary Known Geometry Proc. European Conf. Computer Vision, vol. 3, pp. 272-288, 2002.
[17] Y. Wang and D. Samaras, Estimation of Multiple Directional Light Sources for Synthesis of Mixed Reality Images Proc. Pacific Graphics Conf., pp. 38-47, 2002.
[18] F.R. Gantmacher, The Theory of Matrices. A.M.S. Chelsea Publishing, 1959.
[19] P.V.C. Hough, Methods and Means for Recognising Complex Patterns, US Patent 3 069 654, Dec. 1962.

Index Terms:
Computer vision, illuminant detection, Lambertian sphere limitations, image synthesis.
Citation:
Christos-Savvas Bouganis, Mike Brookes, "Multiple Light Source Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 4, pp. 509-514, April 2004, doi:10.1109/TPAMI.2004.1265865
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