Abstract：An automated Chinese female facial beauty classification approach is presented through the application of machine learning algorithm of C4.5. Seventeen geometric features are designed to abstractly represent each facial image. With large set of 510 Chinese female facial images, high average accuracy of 94.1% is obtained for two-level classification－beautiful or not, and the average accuracy of 4-level classification is 71.6%. The results show that the notion of beauty perceived by human can also be learned by machine through using machine learning techniques.
毛慧芸，金连文，杜明辉. 基于几何特征及C4.5的人脸美丽分类方法[J]. 模式识别与人工智能, 2010, 23(6): 809-814.
MAO Hui-Yun,JIN Lian-Wen,DU Ming-Hui. Facial Beauty Classification Based on Geometric Features and C4.5. , 2010, 23(6): 809-814.
[1] Aharon I, Etcoff N L, Ariely D, et al. Beautiful Faces Have Variable Reward Value: fMRI and Behavioral Evidence. Neuron, 2001, 32(3): 537-551 [2] ODoherty J, Winston J, Critchley H, et al. Beauty in a Smile: The Role of Medial Orbitofrontal Cortex in Facial Attractiveness. Neuropsychologia, 2003, 41(2): 147-155 [3] Zhang Haizhong, Bu Rongfa, Liu Chunmin, et al. The Hypothesis of Aesthetics of the Skull. Chinese Journal of Aesthetic Medicine, 2006, 15(9): 1056-1060 (in Chinese) (张海钟,步荣发,柳春明,等.颅面骨美学假说.中国美容医学, 2006, 15(9): 1056-1060) [4] Luo Weihong, Wang Ren, Fu Minkui. Analysis of the Variales for Facial Profile Esthetics. Journal of Practical Stomatology, 2000, 16 (3): 232-233 (in Chinese) (罗卫红,王 壬,傅民魁.面部侧貌美学特征的调查分析与研究.实用口腔医学杂志, 2000, 16(3): 232-233) [5] Thornhill R, Gangestad S W. Facial Attractiveness. Trends in Cognitive Sciences, 1999, 3(12): 452-460 [6] Rhodes G. The Evolutionary Psychology of Facial Beauty. Annual Review of Psychology, 2006, 57: 199-226 [7] Larglois J H, Kalakanis L, Rubenstein A J, et al. Maxims or Myths of Beauty? A Meta-Analytic and Theoretical Review. Psychological Bulletin, 2000, 126(3): 390-423 [8] Rhodes G, Yoshikawa S, Clark A, et al. Attractiveness of Facial Averageness and Symmetry in Non-Western Cultures: In Search of Biologically Based Standards of Beauty. Perception, 2001, 30(5): 611-625 [9] Aarabi P, Hughes D, Mohajer K, et al. The Automatic Measurement of Facial Beauty // Proc of the IEEE International Conference on System, Man and Cybernetics. Tucson, USA, 2001, Ⅳ: 2644-2647 [10] Irem H, Turkmen Z, Kurt M, et al. Global Feature Based Female Facial Beauty Decision System // Proc of the 15th European Signal Processing Conference. Lausanne, Switzerland, 2007, Ⅰ: 1945-1949 [11] Eisenthal Y, Dror G, Ruppin E. Facial Attractiveness: Beauty and the Machine. Neural Computation, 2006, 18(1): 119-142 [12] Gao Wen, Cao Bo, Shan Shiguang, et al. The CAS-PEAL Large-scale Chinese Face Database and Baseline Evaluations. IEEE Trans on System, Man and Cybernetics, 2008, 38(1): 149- 161 [13] Gunes H, Piccardi M. Assessing Facial Beauty through Proportion Analysis by Image Processing and Supervised Learning. International Journal of Human-Computer Studies, 2006, 64(12): 1184-1199 [14] Berry D S. Attractiveness, Attraction, and Sexual Selection: Evolutionary Perspectives on the Form and Function of Physical Attractiveness. Advances in Experimental Social Psychology, 2000, 32: 273-342 [15] Etcoff N. Survival of the Prettiest: The Science of Beauty. New York, USA: Anchor/Doubleday, 1999 [16] Zhang Xiaomei. Chinese Beauty. Beijing, China: Xinhua Press, 2005 (in Chinese) (张晓梅.中国美.北京:新华出版社, 2005) [17] Alam M, Dover J S. On Beauty Evolution, Psychosocial Considerations, and Surgical Enhancement. ARCH Dermatol, 2001, 137(6): 795-807 [18] Quinlan J R. C4.5: Programs for Machine Learning. San Francisco, USA: Morgan Kaufmann, 1993 [19] Mitchell T M. Machine Learning. New York, USA: McGraw-Hill, 1997 [20] Schmidhuber J. Low-Complexity Art. Journal of the International Society for the Arts, Sciences, and Technology, 1997, 30(2): 97-103
2010, Vol. 23 
