Understanding Color Memory: A Study of Skin Tone Perception in Hue, Intensity, and Chroma

Metadata

Publisher: SMPTE — White Plains, NY, USA
Doc Type: Journal Article
Content Type: Original Research
Abbreviated Title: SMPTE Mot. Imag. J
Volume: 132, No. 6, pp. 19–30
Abstract: Perceptually, one of the strongest memory colors is skin tone. Get it wrong and it is hard to miss. Image adjustments are commonly applied for preference-based image enhancement. Because these adjustments are performed across a variety of color spaces, it is important to understand their effects on skin tone appearance. In this article, results of a psychovisual experiment that explores the perception of skin tone under changes in hue, chroma, and intensity are presented. By combining the effects each axis has on the perception of different skin tones, viewer expectations of color appearance can be evaluated. The experimental results convey a low tolerance for changes in hue when altering intensity and chroma and a high tolerance for changes in intensity across all adjustments. When altering intensity, the results present changes in chroma that follow the shape of the ITU-R BT.2124 (ITP) gamut hull. There was some variability between skin tones. This speaks to how individual skin tone classification may be helpful to preserve appearance following adjustment.
Publication Date: 2023-07-01
DOI: 10.5594/JMI.2023.3277107
ISSN: Print: 1545-0279 | Electronic: 2160-2492
Link: https://doi.org/10.5594/JMI.2023.3277107
Author(s): Jake Zuena
bio
Jake Zuena is an applied vision science engineer at Dolby Laborato?ries, Sunnyvale, CA. In this role, he develops and improves core Dolby imaging technology as well as performs research to model human perception for the design of image-processing algorithms. In 2018, he completed an internship at Warner Bros. Studios, Burbank, CA, in the Emerging Technology Division, focusing on color and imaging science. He received a BS degree in motion picture science from the Rochester Institute of Technology (RIT), Rochester, NY, in 2019. While at RIT, he performed a senior research project to assess the creative preference of highly saturated colors in content mastered for wide color gamut display.
Jaclyn Pytlarz
bio
Jaclyn Pytlarz is a senior staff researcher at Dolby Laboratories, Sunnyvale, CA, where she leads Dolby’s Vision Science Research Organization. Her research includes studying human perception surrounding color mapping, accessibility, and display management algorithms for high dynamic range and wide color gamut imagery. She holds a BS degree in motion picture science from the Rochester Institute of Technology, Rochester, NY, and an MS degree in computational and mathematical engineering from Stanford University, Stanford, CA. Prior to joining Dolby, she worked as an intern for both the Academy of Motion Picture Arts and Sciences, Los Angeles, CA, and iCONN Video Production, Mount Vernon, OH. She has been awarded the IET Best Young Professional Award and the TVNewsCheck Technology Woman to Watch Award and has been elevated to SMPTE Fellow.
Keyword(s): Chroma, Hue, Image Processing, Intensity, Psychophysical Experiment, Skin Tone
Copyright: © 2023 SMPTE

Bibliographic Reference(s)

Hitting the Mark—A New Color Difference Metric for HDR and WCG Imagery [Active]
DCI DCSS v1.4.2 [Superseded*]
IEC 61966-2-1:1999 [Active, Amended]
K. M. Braun, “Memory Color Enhancement Algorithm,” Int. Congr. of Imag. Sci., Rochester, NY, pp. 227–229, May 2006. EXTERNAL
M. Del Barco, “How Kodak’s Shirley Cards Set Photography’s Skin-Tone Standard.” Accessed: Sep. 13, 2022. [Online]. Available: https://www.npr.org/2014/11/13/363517842/for-decades-kodak-s-shirley-cards-set-photography-s-skin-tone-standard EXTERNAL
G. Kindlmann, E. Reinhard, and S. Creem, “Face-Based Luminance Matching for Perceptual Colormap Generation,” IEEE Vis., 2002. VIS 2002, pp. 299–306, 2002, doi:10.1109/ EXTERNAL
C. S. McCamy et al., “A Color-Rendition Chart,” J. Appl. Photographic Eng., 2(3):95–99, 1976. EXTERNAL
T. B. Fitzpatrick, “Soleil et peu,” J. Med. Esthet., 2:33–34, 1975. EXTERNAL
J. L. Hintze and R. D. Nelson, “Violin Plots: A Box Plot-Density Trace Synergism,” Am. Statist., 52(2):181–184, 1998, doi: 10.1080/00031305.1998.10480559. EXTERNAL
R. He et al., “Assessing Skin Tone Heterogeneity Under Various Light Sources,” Proc. of IS&T London Imag. Meeting, London Imag. Meeting 2020 Future Colour Imag., Society for Imaging Science & Technology: London, U.K., Sep. 29–Oct. 1, 2020, doi:10.2352/issn.2694-118X.2020.LIM-15. EXTERNAL
M. Safdar, G. Cui, Y. Kim, and M. Luo, “Perceptually Uniform Color Space for Image Signals Including High Dynamic Range and Wide Gamut,” Opt. Express, 25:15131–15151, 2017. EXTERNAL
“Emoji Modifier Sequence.” Accessed: Jul. 6, 2022. [Online]. Available: https://emojipedia.org/emoji-modifier-sequence/ EXTERNAL
T. Smith and J. Guild, “The C.I.E. Colorimetric Standards and Their Use,” Trans. Opt. Soc., 33(3):73–134, Jan. 1932. EXTERNAL
C. J. Bartleson, “Memory Colors of Familiar Objects*,” J. Opt. Soc. Am., 50:73–77, 1960. EXTERNAL
P. Bodrogi and T. Tarczali, “Colour Memory for Various Sky, Skin, and Plant Colours: Effect of the Image Context,” Color Res. Appl., 26:278–289, May 2001, doi:10.1002/col.1034. EXTERNAL
N. Tsumura et al., “Image-Based Skin Color and Texture Analysis/Synthesis by Extracting Hemoglobin and Melanin Information in the Skin,” ACM SIGGRAPH 2003 Papers (SIGGRAPH ‘03), Association for Computing Machinery: New York, NY, pp. 770–779, 2003, doi:10.1145/1201775.882344. EXTERNAL
“Skin Tone Research @ Google AI.” Accessed: Jul. 6, 2022. [Online]. Available: https://skintone.google/ EXTERNAL
M. D. Fairchild, “Color Appearance Phenomena,” in Color Appearance Models, 2nd ed., M. A. Kriss, Ed., Wiley: Sussex, U.K., pp. 119–122, 2005. EXTERNAL
P. Siple and R. M. Springer, “Memory and Preference for the Colors of Objects,” Perception Psychophys., 34(4):363–370, Oct. 1983. EXTERNAL
ITU-R BT.2100-2 [Active]
R-REC-BT.2124-0 — International Telecommunications Union—Radiocommunication (ITU-R), Recommendation BT.2124-0, “Objective Metric for the Assessment of the Potential Visibility of Colour Differences in Television,” Jan. 2019. EXTERNAL
SMPTE ST 2084:2014 [Active, Stabilized]

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Jake Zuena and Jaclyn Pytlarz; Understanding Color Memory: A Study of Skin Tone Perception in Hue, Intensity, and Chroma, SMPTE Motion Imaging Journal ( Volume: 132, Issue: 6, July 2023); SMPTE, 2023. Available at https://doi.org/10.5594/JMI.2023.3277107

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Jake Zuena and Jaclyn Pytlarz; Understanding Color Memory: A Study of Skin Tone Perception in Hue, Intensity, and Chroma, SMPTE Motion Imaging Journal ( Volume: 132, Issue: 6, July 2023); SMPTE, 2023. Available at https://doi.org/10.5594/JMI.2023.3277107

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<span class="citation">Jake Zuena and Jaclyn Pytlarz; <cite>Understanding Color Memory: A Study of Skin Tone Perception in Hue, Intensity, and Chroma</cite>, SMPTE Motion Imaging Journal ( Volume: 132, Issue: 6, July 2023); SMPTE, 2023. Available at <a href="https://doi.org/10.5594/JMI.2023.3277107" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2023.3277107</a></span>

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Jake Zuena and Jaclyn Pytlarz; Understanding Color Memory: A Study of Skin Tone Perception in Hue, Intensity, and Chroma, SMPTE Motion Imaging Journal ( Volume: 132, Issue: 6, July 2023); SMPTE, 2023
doi: 10.5594/JMI.2023.3277107
url: https://doi.org/10.5594/JMI.2023.3277107

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Jake Zuena and Jaclyn Pytlarz; <cite id="bib-10-5594-jmi-2023-3277107">Understanding Color Memory: A Study of Skin Tone Perception in Hue, Intensity, and Chroma</cite>, SMPTE Motion Imaging Journal ( Volume: 132, Issue: 6, July 2023); SMPTE, 2023
<span class="doi">10.5594/JMI.2023.3277107</span>
</li>