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A Method of Human Facial Portrait Generation Based on Features Exaggeration

  • Xiaorong DuEmail author
  • Jiagui Bai
  • Yong Zhang
  • Yan Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8971)

Abstract

Caricature is the art which has exaggerated feature without losing identifiable characteristics of true face. People like the caricature and the acceptance level is very high, along with the widely used cartoon. But the cartoon drawing is an artistic behavior and ordinary people has not been trained strictly, so it is very hard to draw a caricature for themselves or anyone else. Based on these, automatic generation system is born to simulate the caricature. However, the difficulty lies in feature exaggeration, which involves extracting features and establishing new exaggeration rules, and the current rules are not unified and integrated. So this paper devotes to establishing effective exaggeration rules, and puts it into practice. This paper takes the Thin Plate Spline to conduct the image distortion in order to achieve the face features exaggeration. Taking the Thin Plate Spline to distort image can achieve smooth effect, and then deformation only for exaggerating features, so it makes the computation easy. The source image after image distortion is slightly “real”, so we use Canny operator to extract face image edge, and use binary to keep texture information, which can generate sketch effect. Finally, a lot of tests demonstrate that the effect of face feature exaggeration is very good.

Keywords

Human facial portrait Feature extraction Feature exaggeration Image deformation NPR 

Notes

Acknowledgments.

This paper was supported by “Guangdong Provincial Production Education and Research Major Projects under Grant No.2009A090100025” and “Zhuhai Science and Technology Plan for Production and Research under Grant No.2010B050102021”.

References

  1. 1.
    Shih, Y.C., Paris, S., Barnes, C., Freeman, W.T.: Style transfer for headshot portraits. ACM Trans. Graph. 33(4), 1–14 (2014)CrossRefGoogle Scholar
  2. 2.
    Gambaretto, E., Piña, C.: Real-time animation of cartoon character faces. In: ACM SIGGRAPH 2014 Computer AnimationGoogle Scholar
  3. 3.
    Rhodes, G.: Secrets of the face. N.Z. J. Psychol. 23(1), 3–17 (1994)Google Scholar
  4. 4.
    Sherstinsky, A., Picard, R.: M-Lattice: from morphogenesis to image processing. IEEE Trans. Image Process. 5, 1137–1150 (1996)CrossRefGoogle Scholar
  5. 5.
    Wong, E.C.: Artistic rendering of portrait photographs. Master’s thesis. Cornell University (1999)Google Scholar
  6. 6.
    Brennan, S.: Caricature generator. Master’s thesis. MIT, Cambridge (1982)Google Scholar
  7. 7.
    Koshimizu, H., Tominaga, M., Fujiwara, T., Murakami, K.: On KANSEI facial processing for computerized facial caricaturing system PICASSO. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, pp. 294–299 (1999)Google Scholar
  8. 8.
    Liang, L., Chen, H., Xu, Shum, H.-Y.: Example-Based caricature generation with exaggeration. In: Proceedings of 10th Pacific Conference on Computer Graphics and Applications (2002)Google Scholar
  9. 9.
    Chen, H., Liu, Z., Rose, C., Xu, Y., Shum, H.-Y., Salesin, D.: Example-based composite sketching of human portraits. In: Proceedings of the 3rd International Symposium on Non-Photorealistic Animation and Rendering, June 2004Google Scholar
  10. 10.
    Chiang, P.-Y., Liao, W.-H., Li, T.-Y.: Automatic caricature generation by analyzing facial features. In: Proceedings of Asian Conference on Computer Vision, Korea (2004)Google Scholar
  11. 11.
    Wenjuan, C., Minyong, S., Qingjie, S.: Caricature synthesis and exaggeration based on facial features and their relationship. J. Comput. Aided Des. Comput. Graph. 22(1), 121–128 (2010)CrossRefGoogle Scholar
  12. 12.
    Bookstein, F.L.: Principal warps: Thin-Plate splines and decomposition of deformation. IEEE Trans. Pattern Anal. Mach. Intell. 11, 567–585 (1989)zbMATHCrossRefGoogle Scholar
  13. 13.
    Hassanien, A.E., Nakajima, M.: Image morphing of the facial image transformation based on Navier elastic body splines. In: Proceedings of Computer Animation 1998, Geneva, Switzerland, IEEE Computer Society Press, Los Alamitos, CA, pp. 119–125Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.School of Physics and EngineeringSun Yat-Sen UniversityGuangzhouPeople’s Republic of China
  2. 2.School of Information Science and TechnologySun Yat-Sen UniversityGuangzhouPeople’s Republic of China

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