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http://dx.doi.org/10.5909/JBE.2015.20.4.606

Face Replacement under Different Illumination Condition  

Song, Joongseok (Department of Computer Software, Hanyang University)
Zhang, Xingjie (Department of Computer Software, Hanyang University)
Park, Jong-Il (Department of Computer Software, Hanyang University)
Publication Information
Journal of Broadcast Engineering / v.20, no.4, 2015 , pp. 606-618 More about this Journal
Abstract
Computer graphics(CG) is being important technique in media contents such as movie and TV. Especially, face replacement technique which replaces the faces between different images have been studied as a typical technology of CG by academia and researchers for a long time. In this paper, we propose the face replacement method between target and reference images under different illumination environment without 3D model. In experiments, we verified that the proposed method could naturally replace the faces between reference and target images under different illumination condition.
Keywords
Face replacement; face swapping; face synthesis;
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1 J. Song, X. Zhang, H. Kim, J. Park, "Face Skin Tone Conversion Method Robust to Illumination Changes," 2014 Korean Society of Broadcast Engineers Summer Conference, pp. 71-72, 2014.
2 X. Zhang, J. Song, D. Han, J. Park, ＂The image blending method for face swapping," 2014 Korean Society of Broadcast Engineers Summer Conference, pp. 73-74, 2014.
3 K. Dale, K. Sunkavalli, M. K. Johnson, D. Vlasic, W. Matusik, and H. Pfister, "Video face replacement," Proc. Siggraph Asia, 30(6):130: 1130:10, 2011.
4 D. Bitouk, N. Kumar, S. Dhillon, P. Belhumeur, and S. K. Nayar, “Face swapping: Automatically replacing faces in photographs,” Proc. SIGGRAPH, 27(3);39:139:8, 2008
5 D. Vlasic, M. Brand, H. Pfister, and J. Popovic, “Face transfer with multilinear models,” Proc. SIGGRAPH, 4(3),426433, 2005.   DOI   ScienceOn
6 Garrido, Pablo, et al. "Automatic face reenactment." Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014.
7 W. Matusik et al., “Image-based 3D photography using opacity hulls,” ACM Transactions on Graphics, pp. 427-437, 2002.
8 C. C. Weng, H. Chen, and C.S. Fuh, “A novel automatic white balance method for digital still cameras,” Proc. of IEEE International Symposium on Circuits and Systems, 2005.
9 S. Milborrow and F. Nicolls, “Active shape models with SIFT descriptors and MARS,” Proc. of VISAPP, 2014.
10 L. G. Shapiro and G. C. Stockman, Computer Vision, Prentice Hall, pp.326-340, 2000.
11 R. C. Gonzalez and R. E.Woods, Digial Image Processing, Prentice Hall, 2001.
12 T. Porter and T. Duff, “Compositing Digital Images,” Proc. SIGGRAPH, pp.253-259, 1984.
13 P. Viola and M. J. Jones, “Robust real-time face detection,” International Journal of Computer Vision, 57(2):137-154, 2004.   DOI
14 Hartley, Richard, and Andrew Zisserman, Multiple view geometry in computer vision. Cambridge university press, 2003.
15 V. Blanz, K. Scherbaum, T. Vetter, and H.-P. Seidel,＂Exchanging faces in images," Comp. Graph. Forum, 23(3):669676, 2004.   DOI   ScienceOn
16 O. Alexander. M. Rogers, W. Lambeth, M. Chiang, and P. Debevec, "The Digital Emily Project: photoreal facial modeling and animation," ACM SIGGRAPH Courses, pages 12:1-12:15, 2009.