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The Correlation Between Blood Oxygenation Effects and Human Emotion Towards Facial Skin Colour of Virtual Human

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3D Research

Abstract

The quest for determining the glamorous conditions of the human facial skin based on the texture, color, health perception, races, age and charm is never-ending. Manifestation of facial skin is subjected to the physical and physiological state of human emotions. The facial expression and appearance alters as we move, talk, think and endure stress under constant flux. The colors of skin is one of the key indicators of these changes and the color resolution is decided by the scattering and absorption of light within the skin layers containing chromophores in the melanin and hemoglobin oxygenation in the blood. Understanding the facial color distribution, homogeneity of the pigmentation or skin quality under stimuli are the key issues. We examine the correlation between blood oxygenation in changing facial skin color and basic natural emotional expressions such as angry, happy, sad and fear using the Pulse Oximetry and 3D skin analyzer. The data from seven subjects with three female of age 17, 25 and 35 years, four male of 22, 30, 36, 40 years under different number of partially extreme facial expressions are feed in the new dynamic model for simulation. Experimental results are analyzed to establish a direct relationship between human emotion and facial oxygenation. The strong emotion such as anger is found to stimulate more oxygen under facial skin transforming the face red or rosiness. Furthermore, other emotions assisted with less oxygen concentration create the skin pallor or whitish. Our results in perceiving the human emotions based on facial skin color may contribute towards the development of human aided virtual reality and game environment.

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References

  1. Perrett, D. I., et al. (1998). Effects of sexual dimorphism on facial attractiveness. Nature, 394(6696), 884–887.

    Article  Google Scholar 

  2. Perrett, D. I., et al. (1999). Symmetry and human facial attractiveness. Evolution and Human Behavior, 20(5), 295–309.

    Article  Google Scholar 

  3. Rhodes, G., Sumich, A., & Byatt, G. (1999). Are average facial configurations attractive only because of their symmetry? Psychological Science, 10(1), 52–58.

    Article  Google Scholar 

  4. Fink, B., Grammer, K., & Thornhill, R. (2001). Human (Homo sapiens) facial attractiveness in relation to skin texture and color. Journal of Comparative Psychology, 115(1), 92.

    Article  Google Scholar 

  5. Fink, B., Grammer, K., & Matts, P. J. (2006). Visible skin color distribution plays a role in the perception of age, attractiveness, and health in female faces. Evolution and Human Behavior, 27(6), 433–442.

    Article  Google Scholar 

  6. Jones, B. C., et al. (2004). When facial attractiveness is only skin deep. PERCEPTION-LONDON, 33, 569–576.

    Article  Google Scholar 

  7. Matts, P. J., et al. (2007). Color homogeneity and visual perception of age, health, and attractiveness of female facial skin. Journal of the American Academy of Dermatology, 57(6), 977–984.

    Article  Google Scholar 

  8. Stephen, I. D., et al. (2009). Skin blood perfusion and oxygenation colour affect perceived human health. PLoS One, 4(4), 1.

    Article  Google Scholar 

  9. Russell, R. (2003). Sex, beauty, and the relative luminance of facial features. Perception, 32(9), 1093–1107.

    Article  Google Scholar 

  10. Guowei Hong, M., Luo, R., & Rhodes, P. A. (2001). A study of digital camera colorimetric characterization based on polynomial modeling. Color Research and Application, 26, 76–84.

    Article  Google Scholar 

  11. Anderson, R. R., & Parrish, J. A. (1981). The optics of human skin. Journal of Investigative Dermatology, 77(1), 13–19.

    Article  Google Scholar 

  12. Cotton, S. D., & Claridge, E. (1996). Developing a predictive model of human skin colouring. Proceedings of SPIE, 2708, 814–825.

    Google Scholar 

  13. Mahmud, A. (2012). Dynamic facial appearance capture Using six primaries. Vancouver: The University of British Columbia.

    Google Scholar 

  14. Donner, C., & Jensen, H. W. (2005). Light diffusion in multi-layered translucent materials. In J. Stam (Ed.), ACM transactions on graphics (TOG). Denver: ACM.

    Google Scholar 

  15. Ross, M. H., et al. (2005). Histology: A text and atlas. Baltimore: Williams & Wilkins.

    Google Scholar 

  16. Lever, W. F., & Schaumburg, G. (1990). Histopathology of the Skin. In K. Dabski (Ed.), Granuloma annulare (pp. 257–260). Philadelphia: JB Lippincott Co.

    Google Scholar 

  17. Thornton, M. J. (2002). The biological actions of estrogens on skin. Experimental Dermatology, 11(6), 487–502.

    Article  Google Scholar 

  18. Charkoudian, N., et al. (1999). Influence of female reproductive hormones on local thermal control of skin blood flow. Journal of Applied Physiology, 87(5), 1719–1723.

    Google Scholar 

  19. Liu, D., et al. (1992). Arterial, arterialised venous, venous and capillary blood glucose measurements in normal man during hyperinsulinaemic euglycaemian and hypoglycaemia. Diabetologia, 35, 287–290.

    Article  Google Scholar 

  20. Johnson, J. M. (1998). Physical training and the control of skin blood flow: Adaptations and the control of blood flow with training. Medicine and science in sports and exercise, 30(3), 382–386.

    Article  Google Scholar 

  21. Charkoudian, N. (2003). Skin blood flow in adult human thermoregulation: How it works, when it does not, and why. In T. Lewis (Ed.), Mayo clinic proceedings (pp. 603–612). Philadelphia: Elsevier.

    Google Scholar 

  22. Panza, J. A., et al. (1990). Abnormal endothelium-dependent vascular relaxation in patients with essential hypertension. New England Journal of Medicine, 323(1), 22–27.

    Article  Google Scholar 

  23. Armstrong, N., & Welsman, J. (2001). Peak oxygen uptake in relation to growth and maturation in 11–17 year-old humans. European Journal of Applied Physiology, 85(6), 546–551.

    Article  Google Scholar 

  24. Ponsonby, A. L., Dwyer, T., & Couper, D. (1997). Sleeping position, infant apnea, and cyanosis: A population-based stu. Pediatrics, 99(1), e3–e3.

    Article  Google Scholar 

  25. Greenlees, I., et al. (2008). Soccer penalty takers’ uniform colour and pre-penalty kick gaze affect the impressions formed of them by opposing goalkeepers. Journal of sports sciences, 26(6), 569–576.

    Article  Google Scholar 

  26. Barton, R. A., & Hill, R. A. (2005). Sporting contests: Seeing red? Putting sportswear in context (reply). Nature, 437(7063), E10–E11.

    Article  Google Scholar 

  27. Little, A. C., & Hill, R. A. (2007). Attribution to red suggests special role in dominance signalling. Journal of Evolutionary Psychology, 5(1), 161–168.

    Article  Google Scholar 

  28. Drummond, P. D., & Quah, S. H. (2001). The effect of expressing anger on cardiovascular reactivity and facial blood flow in Chinese and Caucasians. Psychophysiology, 38(2), 190–196.

    Article  Google Scholar 

  29. Elliot, A. J., & Niesta, D. (2008). Romantic red: Red enhances men’s attraction to women. Journal of personality and social psychology, 95(5), 1150.

    Article  Google Scholar 

  30. Rhodesô, G., et al. (2007). Perceived health contributes to the attractiveness of facial symmetry, averageness, and sexual dimorphism. Perception, 36, 1244–1252.

    Article  Google Scholar 

  31. Thornhill, R., & Gangestad, S. W. (1993). Human facial beauty. Human nature, 4(3), 237–269.

    Article  Google Scholar 

  32. Buss, D. M. (1989). Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures. Behavioral and Brain Sciences, 12(1), 1–49.

    Article  Google Scholar 

  33. Leary, M. R., et al. (1992). Social blushing. Psychological Bulletin, 112(3), 446.

    Article  MathSciNet  Google Scholar 

  34. Maddox, K. B., & Gray, S. A. (2002). Cognitive representations of black Americans: Reexploring the role of skin tone. Personality and Social Psychology Bulletin, 28(2), 250–259.

    Article  Google Scholar 

  35. Kelleher, J. F. (1989). Pulse oximetry. Journal of Clinical Monitoring, 5(1), 37–62.

    Article  Google Scholar 

  36. Payne, J. P., & Severinghaus, J. W. (1986). Pulse oximetry. Berlin: Springer.

    Book  Google Scholar 

  37. Jue, T., & Masuda, K. (2013). Application of near infrared spectroscopy in biomedicine. Dijon: Springer.

    Book  Google Scholar 

  38. Martin, L. (1999). All you really need to know to interpret arterial blood gases. Philadelphia: Lippincott Williams & Wilkins.

    Google Scholar 

  39. Rowat, A. M., Dennis, M. S., & Wardlaw, J. M. (2006). Hypoxaemia in acute stroke is frequent and worsens outcome. Cerebrovascular Diseases, 21(3), 166–172.

    Article  Google Scholar 

  40. Zhang, J., et al. (2010). Natural and human-induced hypoxia and consequences for coastal areas: Synthesis and future development. Biogeosciences, 7(5), 1443–1467.

    Article  Google Scholar 

  41. Rabalais, N. N., et al. (2010). Dynamics and distribution of natural and human-caused hypoxia. Biogeosciences, 7(2), 585–619.

    Article  Google Scholar 

  42. Alkawaz, M. H., Mohamad, A. H. D., & Mohamad, F. (2014). Realistic facial expression of virtual human based on color, sweat, and tears effects. The Scientific World Journal,. doi:10.1155/2014/367013.

    Google Scholar 

  43. Hudson, D. M. (2006). Top shelf. Portland: Walch Publishing.

    Google Scholar 

  44. Johns, D. P. P. R. (2003). McGraw-Hill’s pocket guide to spirometry. Roseville: McGraw-Hill.

    Google Scholar 

  45. Donald, E., et al. (1999). Egan’s fundamentals of respiratory care. St. Louis: Mosby.

    Google Scholar 

  46. Ekman, F. (1974). Detecting deception from the body or face. Journal of Personality and Social Psychology, 29, 288–298.

    Article  Google Scholar 

  47. Donner, C., & Jensen, H. W. (2006). A spectral BSSRDF for shading human skin. Proceedings of the 17th Euro graphics conference on rendering techniques. pp. 409–417.

  48. Jimenez, J., et al. (2010). A practical appearance model for dynamic facial color. ACM Transactions on Graphics, 29(6), 1–10.

    Article  Google Scholar 

  49. Donner, C., et al. (2008). A layered, heterogeneous reflectance model for acquiring and rendering human skin. In J. Stam (Ed.), ACM transactions on graphics (TOG). Denver: ACM.

    Google Scholar 

  50. Alkawaz, M. H., Mohamad, D., Basori, A., & Mohamed, F. (2015). A crucial investigation of facial skin colour research trend and direction. International Journal of Multimedia and Ubiquitous Engineering, 10(1), 295–316.

    Google Scholar 

  51. Alkawaz, M., Mohamad, D., Basori, A., & Saba, T. (2015). Blend shape interpolation and FACS for realistic avatar. 3D Research, 6(1), 1–10.

    Article  Google Scholar 

  52. Meethongjan, K., Dzulkifli, M., Rehman, A., Altameem, A., & Altameem, T. (2013). An intelligent fused approach for face recognition. Journal of Intelligent Systems, 22(2), 197–212. doi:10.1515/jisys-2013-0010.

    Article  Google Scholar 

  53. Saba, T., & Altameem, A. (2013). Analysis of vision based systems to detect real time goal events in soccer videos. Applied Artificial Intelligence, 27(7), 656–667.

    Article  Google Scholar 

  54. Saba, T., Rehman, A., & Sulong, G. (2011). Improved statistical features for cursive character recognition. International Journal of Innovative Computing, Information and Control, 7(9), 5211–5224.

    Google Scholar 

  55. Muhsin, Z. F., Rehman, A., Altameem, A., Saba, T., & Uddin, M. (2014). Improved quadtree image segmentation approach to region information. The Imaging Science Journal, 62(1), 56–62.

    Article  Google Scholar 

  56. Mundher, M., Muhamad, D., Rehman, A., Saba, T., & Kausar, F. (2014). Digital watermarking for images security using discrete slantlet transform. Applied Mathematics and Information Sciences, 8(6), 2823–2830. doi:10.12785/amis/080618.

    Article  Google Scholar 

  57. Neamah, K., Mohamad, D., Saba, T., & Rehman, A. (2014). Discriminative features mining for offline handwritten signature verification. 3D Research, 5(3), 1–6. doi:10.1007/s13319-013-0002-3.

    Google Scholar 

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Acknowledgments

Authors are grateful to the Malaysia Ministry of Science and Technology (MOSTI) and Research Management Centre (RMC) of UTM, Department of Informatics, Institut Teknologi Sepuluh Nopember Surabaya, King Abdulaziz University for financial and technical supports.

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Correspondence to Tanzila Saba.

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Alkawaz, M.H., Mohamad, D., Saba, T. et al. The Correlation Between Blood Oxygenation Effects and Human Emotion Towards Facial Skin Colour of Virtual Human. 3D Res 6, 13 (2015). https://doi.org/10.1007/s13319-015-0044-9

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  • DOI: https://doi.org/10.1007/s13319-015-0044-9

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