The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.03 - March (2011 vol.33)
pp: 647-654
Scott McCloskey , McGill University, Montreal
Michael Langer , McGill University, Montreal
Kaleem Siddiqi , McGill University, Montreal
ABSTRACT
This paper examines large partial occlusions in an image which occur near depth discontinuities when the foreground object is severely out of focus. We model these partial occlusions using matting, with the alpha value determined by the convolution of the blur kernel with a pinhole projection of the occluder. The main contribution is a method for removing the image contribution of the foreground occluder in regions of partial occlusion, which improves the visibility of the background scene. The method consists of three steps. First, the region of complete occlusion is estimated using a curve evolution method. Second, the alpha value at each pixel in the partly occluded region is estimated. Third, the intensity contribution of the foreground occluder is removed in regions of partial occlusion. Experiments demonstrate the method's ability to remove the effects of partial occlusion in single images with minimal user input.
INDEX TERMS
Focus, matting, partial occlusion, curve evolution.
CITATION
Scott McCloskey, Michael Langer, Kaleem Siddiqi, "Removal of Partial Occlusion from Single Images", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.33, no. 3, pp. 647-654, March 2011, doi:10.1109/TPAMI.2010.187
REFERENCES
[1] P.E. Debevec and J. Malik, "Recovering High Dynamic Range Radiance Maps from Photographs," Proc. ACM SIGGRAPH, pp. 369-378, 1997.
[2] A.R. Smith and J.F. Blinn, "Blue Screen Matting," Proc. Int'l Conf. Computer Graphics and Interactive Techniques, vol. 30, pp. 259-268, 1996.
[3] N. Asada, H. Fujiwara, and T. Matsuyama, "Seeing Behind the Scene: Analysis of Photometric Properties of Occluding Edges by the Reversed Projection Blurring Model," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 2, pp. 155-167, Feb. 1998.
[4] A. Vasilevskiy and K. Siddiqi, "Flux Maximizing Geometric Flows," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 12, pp. 1565-1578, Dec. 2002.
[5] P. Perona and J. Malik, "Scale-Space and Edge Detection Using Anisotropic Diffusion," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 7, pp. 629-639, July 1990.
[6] M. Grayson, "The Heat Equation Shrinks Embedded Plane Curves to Round Points," J. Differential Geometry, vol. 26, pp. 285-314, 1987.
[7] S. McCloskey, M.S. Langer, and K. Siddiqi, "Automated Removal of Partial Occlusion Blur," Proc. Eighth Asian Conf. Computer Vision, pp. 271-281, 2007.
[8] S. Chaudhuri and A.N. Rajagopalan, Depth from Defocus: A Real Aperture Imaging Approach. Springer-Verlag, 1998.
[9] S.K. Nayar and Y. Nakagawa, "Shape from Focus," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 8, pp. 824-831, Aug. 1994.
[10] Y.Y. Schechner and N. Kiryati, "Depth from Defocus vs. Stereo: How Different Are They Really?" Int'l J. Computer Vision, vol. 39, no. 2, pp. 141-162, 2000.
[11] S. Bhasin and S. Chaudhuri, "Depth from Defocus in Presence of Partial Self Occlusion," Proc. Eighth IEEE Int'l Conf. Computer Vision, pp. 488-493, 2001.
[12] P. Favaro and S. Soatto, "Seeing Beyond Occlusions (and Other Marvels of a Finite Lens Aperture)," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 579-586, 2003.
[13] S. Hasinoff and K. Kutulakos, "A Layer-Based Restoration Framework for Variable-Aperture Photography," Proc. Int'l Conf. Computer Vision, pp. 1-8, 2007.
[14] J. Gu, R. Ramamoorthi, P. Belhumeur, and S. Nayar, "Removing Image Artifacts Due to Dirty Camera Lenses and Thin Occluders," Proc. ACM SIGGRAPH, Dec. 2009.
[15] E. Reinhard and E.A. Khan, "Depth-of-Field-Based Alpha-Matte Extraction," Proc. Symp. Applied Perception in Graphics and Visualization, pp. 95-102, Aug. 2005.
[16] M. McGuire, W. Matusik, H. Pfister, J.F. Hughes, and F. Durand, "Defocus Video Matting," ACM Trans. Graphics, vol. 24, no. 3, pp. 567-576, July 2005.
[17] Y.Y. Chuang, B. Curless, D.H. Salesin, and R. Szeliski, "A Bayesian Approach to Digital Matting," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 264-271, 2001.
[18] J. Sun, J. Jia, C.-K. Tang, and H.-Y. Shum, "Poisson Matting," ACM Trans. Graphics , vol. 23, no. 3, pp. 315-321, Aug. 2004.
[19] A. Levin, D. Lischinski, and Y. Weiss, "A Closed-Form Solution to Natural Image Matting," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 2, pp. 228-242, Feb. 2008.
[20] Y. Zheng, J. Yu, S. Lin, S. Kang, and C. Khambamettu, "Single-Image Vignetting Correction Using Radial Gradient Symmetry," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
[21] A.A. Efros and T.K. Leung, "Texture Synthesis by Non-Parametric Sampling," Proc. IEEE Int'l Conf. Computer Vision, pp. 1033-1038, 1999.
[22] M. Do Carmo, Differential Geometry of Curves and Surfaces. Prentice-Hall, 1976.
[23] G. Sapiro, R. Kimmel, D. Shaked, B. Kimia, and A. Bruckstein, "Implementing Continuous-Scale Morphology via Curve Evolution," Pattern Recognition, vol. 26, no. 9, pp. 1363-1372, Sept. 1993.
[24] B. Kimia, A. Tannenbaum, and S. Zucker, "On the Evolution of Curves via a Function of Curvature. I. The Classical Case," J. Math. Analysis and Applications, vol. 163, pp. 438-458, 1992.
19 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool