Combining a Causal Effect Criterion for Evaluation of Facial Beauty Models

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Abstract

As a data-driven facial beauty modeling method, evolutionary cost-sensitive extreme learning machine presented in Chap.  10 shows the potential of the machine learning methodology in facial beauty analysis.

Keywords

Causal Effect Face Image Local Binary Pattern Linear Manifold Gabor Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. Ahonen T, Hadid A, Pietikainen M (2006) Face description with local binary patterns: application to face recognition. IEEE Trans Pattern Anal Mach Intell 28(12):2037–2041CrossRefMATHGoogle Scholar
  2. Bookstein F (1989) Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans Pattern Anal Mach Intell 11(6):567–585CrossRefMATHGoogle Scholar
  3. Chatterjee S, Hadi AS (1986) Influential observations, high leverage points, and outliers in linear regression. Stat Sci 1(3):379–393MathSciNetCrossRefMATHGoogle Scholar
  4. Chen F, Zhang D (2010) A benchmark for geometric facial beauty study. Springer, pp 21–32Google Scholar
  5. Cootes TF, Edwards GJ, Taylor CJ (2001) Active appearance models. IEEE Trans Pattern Anal Mach Intell 23(6):681–685CrossRefGoogle Scholar
  6. Dryden IL, Mardia KV (1998) Statistical shape analysis. WileyGoogle Scholar
  7. Duda RO, Hart PE, Stork DG (2000) Pattern classification. Wiley InterscienceGoogle Scholar
  8. Eisenthal Y, Dror G, Ruppin E (2006) Facial attractiveness: beauty and the machine. Neural Comput 18(1):119–142CrossRefGoogle Scholar
  9. Fan J, Chau KP, Wan X, Zhai L, Lau E (2012) Prediction of facial attractiveness from facial proportions. Pattern Recogn 45(6):2326–2334CrossRefGoogle Scholar
  10. Gunes H, Piccardi M (2006) Assessing facial beauty through proportion analysis by image processing and supervised learning. Int J Hum Comput Stud 64(12):1184–1199CrossRefGoogle Scholar
  11. He X, Niyogi P (2003) Locality preserving projections. In: Proceedings of neural information processing systems, vol 16, p 153Google Scholar
  12. Kirby M, Sirovich L (1990) Application of the karhunen-loeve procedure for the characterization of human faces. IEEE Trans Pattern Anal Mach Intell 12(1):103–108CrossRefGoogle Scholar
  13. Leyvand T, Cohen-Or D, Dror G, Lischinski D (2008) Data-driven enhancement of facial attractiveness. ACM Trans Graph 27(3):38CrossRefGoogle Scholar
  14. Liao Q, Jin X, Zeng W (2012) Enhancing the symmetry and proportion of 3d face geometry. IEEE Trans Visual Comput Graphics 18(10):1704–1716CrossRefGoogle Scholar
  15. Liu C, Wechsler H (2002) Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition. IEEE Trans Image Process 11(4):467–476CrossRefGoogle Scholar
  16. Nguyen TV, Liu S, Ni B, Tan J, Rui Y, Yan S (2013) Towards decrypting attractiveness via multi-modality cues. ACM Trans Multimedia Comput Commun Appl 9(4):28CrossRefGoogle Scholar
  17. Pallett PM, Link S, Lee K (2010) New “golden” ratios for facial beauty. Vis Res 50(2):149–154CrossRefGoogle Scholar
  18. Perrett D, May K, Yoshikawa S (1994) Facial shape and judgements of female attractiveness. Nature 368(6468):239–242CrossRefGoogle Scholar
  19. Phillips PJ, Moon H, Rizvi SA, Rauss PJ (2000) The feret evaluation methodology for face-recognition algorithms. IEEE Trans Pattern Anal Mach Intell 22(10):1090–1104CrossRefGoogle Scholar
  20. Schaefer S, McPhail T, Warren J (2006) Image deformation using moving least squares. ACM Trans Graph 25(3):533–540CrossRefGoogle Scholar
  21. Schmid K, Marx D, Samal A (2008) Computation of a face attractiveness index based on neoclassical canons, symmetry, and golden ratios. Pattern Recogn 41(8):2710–2717CrossRefGoogle Scholar
  22. Vapnik V (1995) The nature of statistical learning theory. SpringerGoogle Scholar
  23. Zhang D, Zhao Q, Chen F (2011) Quantitative analysis of human facial beauty using geometric features. Pattern Recogn 44(4):940–950CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.The Hong Kong Polytechnic UniversityHung HomHong Kong
  2. 2.Tsinghua UniversityShenzhenChina
  3. 3.Harbin Institute of TechnologyShenzhenChina

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