ABSTRACT
To a certain extent, modern aesthetics force people to change the shape and color of eyebrows according to the current popular form, and achieve the aesthetic effect of the overall effect. How to match the appropriate eyebrows according to different face types has always been pursued and desired by people. However, hand animation eyebrows require certain skills. Not everyone can draw beautiful and clean eyebrows. In order to meet the requirements of automation and real-time in virtual makeup technology, this paper proposes an algorithm for automatically modifying eyebrows by using digital image processing technique. Firstly, the Haar classifier and the Dajin threshold method combined with the Haar-Like feature and the AdaBoost algorithm are used to realize the detection, segmentation and replacement of the eyebrows. At the same time, the color transformation can be performed to achieve further modification effects. Through the experimental results, it can be found that the proposed automatic modification algorithm not only realize the automatic modification of eyebrows and the transformation of different colors, but also the makeup effect is natural and beautiful.
- Xu, L., Du, Y. Z., and Zhang, Y. M. 2013. An automatic framework for example-based virtual makeup. In Proceedings of 2013 IEEE International Conference on Image Processing (Melbourne, VIC, Australia, September 15-18, 2013). IEEE, DOI= https://doi.org/10.1109/ICIP.2013.6738660.Google ScholarCross Ref
- Zhang, C., Li, S. and Zhao, T. 2019.Cascaded regression using landmark displacement for 3D face reconstruction. PATTERN RECOGNITION LETTERS, 125(JUL. 2019). DOI= https://doi.org/10.1016/j.patrec.2019.07.017Google ScholarDigital Library
- Zhang, C., and Li, Y. 2009. Eyebrow image segmentation method based on semi-supervised learning (in Chinese). Computer Engineering and Application. 45, 21 (JUL 2009), 139--141. DOI= https://doi.org/10.1016/j.commatsci.2008.04.030.Google Scholar
- Boykov, Y. Y. and Jolly, M. P. 2001. Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. In Proceeding of the 8th International Conference on Computer Vision (Vancouver, BC, United states, July, 09-12, 2001), 105--112. DOI= https://doi.org/10.1109/ICCV.2001.937505.Google Scholar
- Li, Y. Sun, J. and Tang, C. K. 2004. Lazy snapping. In Proceedings of the ACM SIGGRAPH 2004 (Los Angeles, CA, United states, August 08-12, 2004) ACM Transactions on Graphics - Proceedings of ACM SIGGRAPH 2004, 3030--308. DOI= https://doi.org/10.1145/1015706.1015719.Google ScholarDigital Library
- Li, Y., Zhang, X., and Zhang, C. 2011. Semi-automatic eyebrow recognition method (in Chinese). Computer Engineering and Applications, 47, 31, (Oct. 2011), 201--205.Google Scholar
- Zhu, X., Su, S. and Fu, M. 2019. A density-watershed algorithm (DWA) method for robust, accurate and automatic classification of dual-fluorescence and four-cluster droplet digital PCR data. ANALYST, 144, 16(AUG. 2019), 4757--4771.Google Scholar
- Ren, J., Ren, B. and Zhang, Q.2019. A Novel Hybrid Extreme Learning Machine Approach Improved by K Nearest Neighbor Method and Fireworks Algorithm for Flood Forecasting in Medium and Small Watershed of Loess Region. WATER, 11, 9(SEP. 2019).Google Scholar
- Xie, H., Zhang, L., and Lim, CP. 2019. Improving K-means clustering with enhanced Firefly Algorithms APPLIED SOFT COMPUTING, 84(Nov. 2019). DOI= https://doi.org/10.1016/j.asoc.2019.105763.Google ScholarDigital Library
- Zhang, X., Li, Y., and Zhang, C. 2012. Positive semi-supervised learning eyebrow image segmentation (in Chinese). Computer and modernization, 9(JUL. 2012), 127--133.Google Scholar
- Li, J., and Li, Y. 2010. Eyebrow detection and positioning based on AdaBoost (in Chinese). Computer and digital engineering, 38, 8(AUG. 2010), 175--176+200.Google Scholar
- Phtm, T.M., Doan, D.C. and Hitzer, E. 2019. Feature Extraction Using Conformal Geometric Algebra for AdaBoost Algorithm Based In-plane Rotated Face Detection. ADVANCES IN APPLIED CLIFFORD ALGEBRAS, 29, 4(SEP. 2019) DOI=https://doi.org/10.1007/s00006-019-0976-x.Google Scholar
- Freund, Y., and Schapire, R. E. 1995. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. In Proceeding of the 2nd European Conference on Computational Learning Theory (Barcelona, Spain, March 13-15, 1995), Computational Learning Theory - 2nd European Conference, EuroCOLT 1995, Proceedings, 23--37.Google ScholarCross Ref
- Zhou, L., and Jiang, F. 2017. A Survey of Image Segmentation Methods (in Chinese). Application Research of Computers, 34, 7(Nov. 2017), 1921--1928.Google Scholar
- Sreedhar, K., Katta, R., and Linga, R. 2019. A Review of Image Denoising and Segmentation Methods Based on Medical Images. International Journal of Machine Learning and Computing, 9, 3(2019), 288--295.Google ScholarCross Ref
Index Terms
- Research on Image-based Automatic Modification Algorithm of Eyebrows
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