312 JOURNAL OF COSMETIC SCIENCE Model proved to be an effective way to study consumer-perceivable skin properties. The methods, models, and results reported in this study provide a way to link results of panel evaluation and objective measurement to enrich the derived ideal complexion score with consumer relevance. NOTE: Part of this study was presented at the 26th IFSCC Conference, October 18–27, 2021 (paper ID: SS_626). REFERENCES (1) L. Ang, B. J. Lee, H. Kim, and M. H. Yim, Prediction of hypertension based on facial complexion, Diagnostics, 11, 540 (2021). (2) Y. Umeda-Kameyama, M. Kameyama, T. Tanaka, B. Son, T. Kojima, M. Fukasawa, T. Iizuka, S. Ogawa, K. Iijima, and M. Akishita, Screening of Alzheimer’s disease by facial complexion using artificial intelligence, Aging, 13, 1765–1772 (2021). (3) C. Zhao, G. Li, F. Li, Z. Wang, and C. Liu, Qualitative and quantitative analysis for facial complexion in traditional Chinese medicine, BioMed Res. Int., 2014, 207589 (2014). (4) Q. Huixia, L. Xiaohui, Y. Chengda, Z. Yanlu, J. Senee, A. Laurent, R. Bazin, F. Flament, A. Adam, and B. Piot, Instrumental and clinical studies of the facial skin tone and pigmentation of Shanghaiese women. Changes induced by age and a cosmetic whitening product, Int. J. Cosmet. Sci., 34, 49–54 (2012). (5) A. Little, B. Jones, and L. DeBruine, Facial attractiveness: evolutionary based research. Philos. Trans. R Soc. B Biol. Sci., 366, 1638–1659 (2011). (6) B. Ghani, R. Jouhar, and N. Ahmed, Relationship of facial skin complexion with gingiva and tooth shade on smile attractiveness, J. Interdiscipl. Med. Dent. Sci., 4, 5 (2016). (7) A. S. Krishen, M. S. LaTour, and E. J. Alishah, Asian females in an advertising context: exploring skin tone tension, J. Curr. Issues Res. Advert., 35, 71–85 (2014). (8) Q. Xie and M. Zhang, White or tan? A cross-cultural analysis of skin beauty advertisements between China and the United States, Asian J. Commun., 23, 538–554 (2013). (9) A. Coondoo and R. Sarkar, The unhealthy obsession with fairness and the menace of fairness creams in India, Pigment Int., 8, 4–7 (2020). (10) C. A. D. Charles, Skin bleaching and the prestige complexion of sexual attraction, Sex. Cult., 15, 375–390 (2011). (11) Y. Kobayashi, S. Matsushita, and K. Morikawa, Effects of lip color on perceived lightness of human facial skin, i-Perception, 2017, July–August, 1–10 (2017). (12) A. Saeed, S. Maqsood, and A. Rafique, Color matters: field experiment to explore the impact of facial complexion in Pakistani labor market, Journal of the Asia Pacific Economy, 24, 347–363 (2019). (13) S. Ismail, S. Loya, and J. Hussain, Obsession for fair skin color in Pakistan, International Journal of Innovation and Research in Educational Sciences, 2, 2349–5219 (2015). (14) E. Li, H. Min, R. Belk, J. Kimura, and S. Bahl, Skin lightening and beauty in four Asian cultures, Adv. Consum. Res., 35, 444–449 (2008). (15) A. Saeed, S. Maqsood, and A. Rafique, The effects of sleep deprivation on the biophysical properties of facial skin, J. Cosmet. Dermatol. Sci. Appl., 7, 34–47 (2017). (16) S. I. Jang, M. Lee, J. Han, J. Kim, A. R. Kim, J. S. An, J. O. Park, B. J. Kim, and E. Kim, A study of skin characteristics with long-term sleep restriction in Korean women in their 40s, Skin Res. Technol., 26, 193–199 (2020). (17) L. M. Lu, X. Chen, and J. T. Xu, Determination methods for inspection of the complexion in traditional Chinese medicine: a review, Chin. J. Integr. Med., 7, 701–705 (2009). (18) T. Wu, B. Bai, F. Sun, C. Zhou, and P. Wang, Study on complexion recognition in TCM, 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, IEEE Xplore (2010).
313 Characterizing and Modeling Complexion (19) W. S. Li, S. Wang, T. Wu, and Y. Wu, Facial complexion recognition based on supervised latent dirichlet allocation in TCM, 2011 4th International Conference on Biomedical Engineering and Informatics, IEEE Xplore (2011). (20) C. Liu, C. Zhao, G. Li, F. Liz, and Z. Wang, Computerized color analysis for facial diagnosis in traditional Chinese medicine, 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE Xplore (2013). (21) X. Li, F. Li, Y. Wang, P. Qian, and X. Zheng, Computer-aided disease diagnosis system in TCM based on facial image analysis, Int. J. Funct. Inform. Personal. Med., 2, 303–314 (2009). (22) Y. Lin, Complexion classification based on convolutional neural network, J. Artif. Intell. Pract., 3, 22–30 (2020). (23) J. F. Hermanns, L. Petit, T. Hermanns-Le, and G. E. Pierard, Analytic quantification of phototype- related regional skin complexion, Skin Res. Technol., 7, 168–171 (2001). (24) J. de Rigal, M. L. Abella, F. Giron, L. Caisey, and M. A. Lefebvre, Development and validation of a new skin color chart, Skin Res. Technol., 13, 101–109 (2007). (25)V .Hourblin, S. Nouveau, N. Roy, and O. de Lacharrière, Skin complexion and pigmentary disorders in facial skin of 1204 women in 4 Indian cities, Indian J. Dermat. Venereol. Leprol., 80, 395–401 (2014). (26) L. Ang, B. J. Lee, H. Kim, and M. H. Yim, STOP: a spectroscopic tip optical probe for skin complexion characterization, Biomedical Optics Conference 2016, OSA Technical Digest (2016). (27) Y. Wu, T. Tanaka, and M. Akimoto, Utilization of individual typology angle (ITA) and hue angle in the measurement of skin color on images, Bioimages, 28, 1–7 (2020). (28) C. Musnier, P. Piquemal, P. Beau, and J. C. Pittet, Visual evaluation in vivo of ‘complexion radiance’ using the C.L.B.T. sensory methodology, Skin Res. Technol., 10, 50–56 (2004). (29) A. Petitjean, J. M. Sainthillier, S. Mac-Mary, P. Muret, B. Closs, T. Gharbi, and P. Humbert, Skin radiance: how to quantify? Validation of an optical method, Skin Res. Technol., 13, 2–8 (2007). (30) D. Qu, X. Wang, J. Liu, Z. Wu, C. Kuesten, W. Hu, H. Totsuka, and Y. Chen, Comprehensive model for characterizing skin translucency by expert grading, panel evaluation and image analysis in a Chinese population, Int. J. Cosmet. Sci., 44, 500–513 (2022). (31) Z. Wu, D. Qu, S. Whitehead, X. Wang, and J. Liu, Quantification of perception towards facial skin ideal complexion in multiple ethnic populations from clinical imaging cues, Int. J. Cosmet. Sci., 44, 636–649 (2022). (32) D. Qu and C. Kuesten, Development, validation and application of an image analysis method for in vivo measurement of skin visual roughness, Anti-Ageing Skin Care Conference 2018, London, UK, June 5–6, paper no. 6 (2018). (33) D. Qu and Y. Park, Skin youthfulness index – a novel model correlating age with objectively measured visual parameters of facial skin, IFSCC Magazine, 17, 9–16 (2014). (34) A. Matsubara, Skin translucency: what is it and how is it measured? 24th IFSCC Congress Abstracts (Oral Session), Osaka, Japan, 92–93 (2006). (35) A. Brown and A. Maydeu-Olivares, Item response modeling of forced-choice questionnaires, Educ. Psychol. Meas., 71(3), 460–502 (2011). (36) J. Bi and C. Kuesten, Sensory measurements for the method of “M+N” with larger M and N, J. Sens. Stud., 30, 461–471 (2015). (37) J. M. Bland and D. G. Altman, The odds ratio, BMJ, 320, 1468 (2000). (38) R. A. Bradley and M. Terry. The rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39, 324–345 (1952). (39) A. Agresti, “Bradley–Terry Model for paired preferences,” in Categorical Data Analysis, D. J. Balding, N. A. C. Cressie, and G. M. Fitzmaurice, Eds., Wiley, New York, 1990, 436–439. (40) Bradley–Terry Model, Wikipedia, accessed December 2022, https://en.wikipedia.org/wiki/ Bradley%E2%80%93Terry_model.
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