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Region-based Face Makeup using two example face images
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 Title & Authors
Region-based Face Makeup using two example face images
Lee, Jae-Yoon; Kang, Hang-Bong;
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 Abstract
In this paper, we propose a new method of eye, face, and lip makeup techniques on the target face image from several makeup examples without losing detail features such as eyelids, eyebrows, hair. After detection of the feature layer for the skin, we applied our makeup techniques to the target face by using a blending technique. We used a cartoon rendering using bilateral filter. In order to smoothly makeup the target face, we created two Gaussian Weight maps for natural skin makeup effects. Our method did not need to perform complex operations, so the makeup results are so natural. Our experimental results show good performances in various makeups.
 Keywords
Digital Makeup;Region Based Makeup;Blending;Gaussian Weight;
 Language
Korean
 Cited by
 References
1.
S.Y. Cho and S.Y. Shin, “The Analysis of Research Themes and Area of Treatises concerning Make-up Studies,” Journal of the Korean Beauty Art Society, Vol. 5, No. 5, pp 205-214, 2011.

2.
H. Winnemoller, “Real-time Video Abstraction,” Journal of Special Interest Group on GRAPHics and Interactive Techniques, Vol. 25, No. 3, pp. 1221-1226, 2006.

3.
W.S. Tong, C.K. Tang, M.S. Brown, and Y.Q. Xu, “Example-based Cosmetic Transfer,” Proceeding of Pacific Computer Graphics and Applications, pp. 211-218, 2007.

4.
M.L. Eckert, N. Kose, and J.L. Dugelay, “Facial Cosmetics Database and Impact Analysis on Automatic Face Recognition,” Proceeding of IEEE International Workshop on Multimedia Signal Processing, pp. 434-439, 2013.

5.
K. Scherbaum, T. Ritschel, M. Hullin, T. Thormahlen, V. Blanz, and H.P. Seidel, “Computer-suggested Facial Makeup,” Eurographics, Vol. 30, No. 2, pp. 485-492, 2011.

6.
A. Dhall, G. Sharma, R. Bhatt, and G.M. Khan, “Adaptive Digital Makeup,” International Symposium on Advances in Visual Computing, pp. 728-736, 2009.

7.
M.J. Kim "An Image-based Color Appearance Analysis of Makeup and Image Synthesis based on Kubelka-Munk Model," Journal of Korea Multimedia Society, Vol. 18, No. 3, pp. 349-358, 2015 crossref(new window)

8.
D. Guo and T. Sim, “Digital Face Makeup by Example,” Proceeding of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 73-79, 2009.

9.
Z. Liu, Z. Zhang, and Y. Shan, “Image-based Surface Detail Transfer,” Computer Graphics and Application, Vol. 24, No. 3, pp. 30-35, 2001.

10.
Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, “Edge-preserving Decompositions for Multi-scale Tone and Detail Manipulation,” ACM Transactions on Graphics, Vol. 27, No. 3, pp. 1-10, 2008. crossref(new window)

11.
Makeup Journal, http://makeupjournal.net/, (accessed Mar. 6, 2015)

12.
TAAZ The Brains Behind The Beauty, http://www.taaz.com/ (accessed Mar. 6, 2015)

13.
F. Bookstein, “Principal Warps: Thin-plate Splines and the Decomposition of Deformations,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, No. 6, pp. 567-585, 1989. crossref(new window)

14.
S. Milborrow and F. Nicolls, “Locating Facial Features with an Extended Active Shape Model,” Proceeding of the European Conference on Computer Vision, Vol. 5305, pp. 504-513, 2008.

15.
T.F. Cootes, G.J. Edwards, and C.J. Taylor, “Active Appearance Models,” Proceeding of the European Conference on Computer Vision, Vol. 2, pp. 484-498, 2004.

16.
X. Xiong and F.D. Torre, “Supervised Descent Method and Its Applications to Face Alignment,” Proceeding of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 532-539, 2013.