Predicting Facial Attractiveness from Colour Cues: A New Analytic Framework.

Various facial colour cues were identified as valid predictors of facial attractiveness, yet the conventional univariate approach has simplified the complex nature of attractiveness judgement for real human faces. Predicting attractiveness from colour cues is difficult due to the high number of candidate variables and their inherent correlations. Using datasets from Chinese subjects, this study proposed a novel analytic framework for modelling attractiveness from various colour characteristics. One hundred images of real human faces were used in experiments and an extensive set of 65 colour features were extracted. Two separate attractiveness evaluation sets of data were collected through psychophysical experiments in the UK and China as training and testing datasets, respectively. Eight multivariate regression strategies were compared for their predictive accuracy and simplicity. The proposed methodology achieved a comprehensive assessment of diverse facial colour features and their role in attractiveness judgements of real faces; improved the predictive accuracy (the best-fit model achieved an out-of-sample accuracy of 0.66 on a 7-point scale) and significantly mitigated the issue of model overfitting; and effectively simplified the model and identified the most important colour features. It can serve as a useful and repeatable analytic tool for future research on facial impression modelling using high-dimensional datasets.

Research on the interactive perception of color paper-cutting culture rendering based on AR.

To address the digital medium preference of the millennial generation, this study utilizes augmented reality (AR) technology for rendering color paper cuttings by developing a mobile terminal based on Unity 3D and 3ds Max to demonstrate digital works scanned by paper-cutting entities. Three subjective scaling experiments are conducted to evaluate the aesthetics, viewership, and impression of four genres of digital color paper cutting. The results show that observers have more preference for warm background with the maximum scaling value at the 7.5 mm/s playback speed and a specific superimposed order. Importantly, current experimental design and interactive evaluation provide a reference for AR display parameters.

Digital Grading the Color Fastness to Rubbing of Fabrics Based on Spectral Reconstruction and BP Neural Network.

To digital grade the staining color fastness of fabrics after rubbing, an automatic grading method based on spectral reconstruction technology and BP neural network was proposed. Firstly, the modeling samples are prepared by rubbing the fabrics according to the ISO standard of 105-X12. Then, to comply with visual rating standards for color fastness, the modeling samples are professionally graded to obtain the visual rating result. After that, a digital camera is used to capture digital images of the modeling samples inside a closed and uniform lighting box, and the color data values of the modeling samples are obtained through spectral reconstruction technology. Finally, the color fastness prediction model for rubbing was constructed using the modeling samples data and BP neural network. The color fastness level of the testing samples was predicted using the prediction model, and the prediction results were compared with the existing color difference conversion method and gray scale difference method based on the five-fold cross-validation strategy. Experiments show that the prediction model of fabric color fastness can be better constructed using the BP neural network. The overall performance of the method is better than the color difference conversion method and the gray scale difference method. It can be seen that the digital rating method of fabric staining color fastness to rubbing based on spectral reconstruction and BP neural network has high consistency with the visual evaluation, which will help for the automatic color fastness grading.

Domain and range of the CIECAM16 forward transformation.

The domain and range of the CIECAM16 forward transformation was numerically determined and visualized for CIE standard illuminants, using a linear programming approach that provides the gamuts and colour solids for optimum colours. The effect of the surround, adapting luminance, and luminance of the background on the range of the CIECAM16 forward transformation were individually analyzed, showing that their ranges increased when the surround changed from dark to dim or average, the adapting luminance increased, or the luminance of the background decreased. The proposed methodology for the determination and visualization of the domain and range of the CIECAM16 forward transformation can be used for any illuminant, as well as for CIECAM02, CAM16, CAM02-UCS and CAM16-UCS. The findings of this paper not only solve the long-term unresolved domain and range problems of the CIE colour appearance models, but also find applications in cross-media colour reproduction. Furthermore, it was also found that some non-CIE colours are inside the International Color Consortium Profile Connection Space (ICC PCS), and some CIE colours are not included in that space.

Spectra Reconstruction for Human Facial Color from RGB Images via Clusters in 3D Uniform CIELab* and Its Subordinate Color Space.

Previous research has demonstrated the potential to reconstruct human facial skin spectra based on the responses of RGB cameras to achieve high-fidelity color reproduction of human facial skin in various industrial applications. Nonetheless, the level of precision is still expected to improve. Inspired by the asymmetricity of human facial skin color in the CIELab* color space, we propose a practical framework, HPCAPR, for skin facial reflectance reconstruction based on calibrated datasets which reconstruct the facial spectra in subsets derived from clustering techniques in several spectrometric and colorimetric spaces, i.e., the spectral reflectance space, Principal Component (PC) space, CIELab*, and its three 2D subordinate color spaces, La*, Lb*, and ab*. The spectra reconstruction algorithm is optimized by combining state-of-art algorithms and thoroughly scanning the parameters. The results show that the hybrid of PCA and RGB polynomial regression algorithm with 3PCs plus 1st-order polynomial extension gives the best results. The performance can be improved substantially by operating the spectral reconstruction framework within the subset classified in the La* color subspace. Comparing with not conducting the clustering technique, it attains values of 25.2% and 57.1% for the median and maximum errors for the best cluster, respectively; for the worst, the maximum error was reduced by 42.2%.

Optimizing Color-Difference Formulas for 3D-Printed Objects.

Based on previous visual assessments of 440 color pairs of 3D-printed samples, we tested the performance of eight color-difference formulas (CIELAB, CIEDE2000, CAM02-LCD, CAM02-SCD, CAM02-UCS, CAM16-LCD, CAM16-SCD, and CAM16-UCS) using the standardized residual sum of squares (STRESS) index. For the whole set of 440 color pairs, the introduction of kL (lightness parametric factor), b (exponent in total color difference), and kL + b produced an average STRESS decrease of 2.6%, 26.9%, and 29.6%, respectively. In most cases, the CIELAB formula was significantly worse statistically than the remaining seven formulas, for which no statistically significant differences were found. Therefore, based on visual results using 3D-object colors with the specific shape, size, gloss, and magnitude of color differences considered here, we concluded that the CIEDE2000, CAM02-, and CAM16-based formulas were equivalent and thus cannot recommend only one of them. Disregarding CIELAB, the average STRESS decreases in the kL + b-optimized formulas from changes in each one of the four analyzed parametric factors were not statistically significant and had the following values: 6.2 units changing from color pairs with less to more than 5.0 CIELAB units; 2.9 units changing the shape of the samples (lowest STRESS values for cylinders); 0.7 units changing from nearly-matte to high-gloss samples; and 0.5 units changing from 4 cm to 2 cm samples.

Influences of shape, size, and gloss on the perceived color difference of 3D printed objects.

In order to study the influence and mechanisms of color differences using 3D-shaped objects, 440 pairs of 3D samples surrounding five CIE color centers (gray, red, yellow, green, and blue) with the variations of gloss, size, and shape were prepared by a Sailner 3D color printer, and their color differences were assessed by 26∼45 observers using the gray-scale method. The new color difference data were used to investigate the parametric effects (gloss, 3D shape, and size) on the perceived color difference. Results indicate that, for 3D objects, high gloss and small size objects (2 cm) raise smaller visual color differences than matte and large size objects (4 cm), and the visual color difference of spheres is larger than that of the cone and cylinder sample pairs. The chromaticity ellipses indicated that the glossy samples with different shapes will arouse fairly different visual perceptions, especially for sphere and cylinder samples.

Interim connection space based on colorimetric values for spectral image compression and reproduction.

A new interim and connection space (ICS) and its reconstruction method are proposed. The proposed ICS,tD65A, consists of six colorimetric values or two sets of tristimulus values under CIE illuminant D65 and A respectively. In addition, a new spectral decomposition based on the tD65A ICS and the Wiener Estimation matrix MW was introduced for an improved spectral reconstruction. Accompanying the tD65A ICS, m important basis vectors for the metameric black space based on the new spectral decomposition, and a mapping matrix MP,k via a polynomial model of order k, were trained so that both the spectral and colorimetric accuracies for the reconstructed reflectance can be further enhanced. The proposed ICS and its reconstruction method can ensure exact colorimetric matches under two (real rather than synthetic) illuminants D65 and A, which is an advantage compared with other ICSs. The performance of the proposed method was tested and compared with five other ICSs using the NCS dataset and three spectral images respectively, using RMSE and GFC to measure the spectral accuracy, and using CIEDE2000 colour differences to measure the colorimetric accuracy under three types of illuminants (continuous, fluorescent, and LED). Performance test results showed the proposed methods outperform other ICSs in terms of both spectral accuracy and colorimetric measures (RMSE, GFC, and CIEDE2000 colour difference). Therefore, it is expected the proposed ICS and its reconstruction method can play an important role in spectral image compression and reproduction applications.

Developing a digital archive system for imperial Chinese robe in the Qing Dynasty.

The digital archive of cultural heritage provides new opportunities for the protection of the cultural heritage and the development of online museums. One of the essential requirements for the digitization is to achieve accurate color reproduction. Taking the Imperial Chinese robes in the Qing Dynasty as an example, this study aims to develop a digital achieve system to digitize the robes using a high-end imaging system and accurately reproduce their color properties on a display. Currently, there has been very limited study focused on the color reproduction of silk fabrics or other textile materials. The conventional color management process using a traditional color chart, however, may not be suitable for the reproduction of silk fabrics because they have very high gloss. To address this difficulty, a unique "Qianlong Palette" color chart, consisting of 210 silk fabric samples, has been specifically produced for optimizing the color reproduction of silk fabrics and a color image reproduction system has been developed for the digitization and archiving of the clothing fabric for the royal court. Color characterization models using both the "Qianlong Palette" color chart and the traditional color chart, and different mapping methods, are compared and the model with highest accuracy used in a self-programmed interface for automatically processing textile images in the future. Finally, the digital archive system has been validated using six garments of silk fabric relics. The color differences after the color image reproduction are all less than 3.00ΔE* ab , indicating acceptable color reproduction of the system. The images after color reproduction have also been evaluated subjectively by experts from the museum and the results are considered satisfactory. Our results show that the newly designed "Qianlong Palette" color chart exhibits superior performance over the conventional color chart in effectively predicting the color of the silk fabrics. The self-programmed graphical user interface for image color management can serve as a powerful tool to truly reproduce the color of various silk fabric relics in museums in the future and digitally archive those valuable cultural relics for different uses.

Different colour predictions of facial preference by Caucasian and Chinese observers.

Facial colour characteristics convey vital personal information and influence social interactions and mate choices as contributing factors to perceived beauty, health, and age. How various colour characteristics affect facial preference and whether there are cultural differences are not fully understood. Here, we provide a useful and repeatable methodology for skin colour research based on a realistic skin model to investigate the effect of various facial colour characteristics on facial preference and compare the role of colour predictors in Caucasian (CA) and Chinese (CN) samples. Our results show that, although the average skin colour of facial areas plays a limited role, together with colour variation and contrast, there are stronger links between colour and facial preference than previously revealed. We also find large cultural differences in facial colour perceptions; Chinese observers tend to rely more heavily on colour and lightness cues to judge facial preference than Caucasian observers.

Optimizing Parametric Factors in CIELAB and CIEDE2000 Color-Difference Formulas for 3D-Printed Spherical Objects.

The current color-difference formulas were developed based on 2D samples and there is no standard guidance for the color-difference evaluation of 3D objects. The aim of this study was to test and optimize the CIELAB and CIEDE2000 color-difference formulas by using 42 pairs of 3D-printed spherical samples in Experiment I and 40 sample pairs in Experiment II. Fifteen human observers with normal color vision were invited to attend the visual experiments under simulated D65 illumination and assess the color differences of the 82 pairs of 3D spherical samples using the gray-scale method. The performances of the CIELAB and CIEDE2000 formulas were quantified by the STRESS index and F-test with respect to the collected visual results and three different optimization methods were performed on the original color-difference formulas by using the data from the 42 sample pairs in Experiment I. It was found that the optimum parametric factors for CIELAB were kL = 1.4 and kC = 1.9, whereas for CIEDE2000, kL = 1.5. The visual data of the 40 sample pairs in Experiment II were used to test the performance of the optimized formulas and the STRESS values obtained for CIELAB/CIEDE2000 were 32.8/32.9 for the original formulas and 25.3/25.4 for the optimized formulas. The F-test results indicated that a significant improvement was achieved using the proposed optimization of the parametric factors applied to both color-difference formulas for 3D-printed spherical samples.

Skin color measurements before and after two weeks of sun exposure.

We performed spectrophotometric measurements of skin reflectance at four body locations (forehead, cheek, neck, and back of hand), before and after two weeks of sun exposure, for 103 first-year college students. Skin reflectance was measured twice at each body location, before and after two weeks of sun exposure, obtaining an average repeatability (mean color difference from the mean) in the range of 0.2-0.5 CIELAB units (D65 illuminant, CIE 1931 standard observer). However, the average skin color differences before and after two weeks of sun exposure were in the range of 3.6-3.9 CIELAB units, considerably higher than measured repeatability, as a consequence of suntanning. Skin color appearance variation was analyzed in the CIELAB color space, and it was found that at all body locations two weeks of sun exposure made lightness L∗ and hue-angle hab significantly decrease, a∗ and chroma Cab∗ significantly increase, and b∗ shows no statistically significant changes (except for hab at the forehead and cheek, and for a∗ at the forehead where no statistically significant changes were found). An W shape for skin spectral reflectance between 520 nm and 600 nm was found at some of the four measured body locations. It was found that the individual typological angle (ITA) defined from L∗ and b∗ performed well in predicting our measured data and a modification of ITA using L∗ and Cab∗ performed even better, with the measured L∗ as reference. The color shifts produced by two weeks of sun exposure in different planes of CIELAB were analyzed for the skin categories established by the ITA index, and compared with the control group data accumulated by Amano et al. (PLoS ONE. 15(12), e0233816)(PLoS ONE 15(2020) e0233816). The measured skin spectra can be useful to the skin color database currently being developed by CIE TC 1-92.

Spectral Reconstruction Using an Iteratively Reweighted Regulated Model from Two Illumination Camera Responses.

An improved spectral reflectance estimation method was developed to transform captured RGB images to spectral reflectance. The novelty of our method is an iteratively reweighted regulated model that combines polynomial expansion signals, which was developed for spectral reflectance estimation, and a cross-polarized imaging system, which is used to eliminate glare and specular highlights. Two RGB images are captured under two illumination conditions. The method was tested using ColorChecker charts. The results demonstrate that the proposed method could make a significant improvement of the accuracy in both spectral and colorimetric: it can achieve 23.8% improved accuracy in mean CIEDE2000 color difference, while it achieves 24.6% improved accuracy in RMS error compared with classic regularized least squares (RLS) method. The proposed method is sufficiently accurate in predicting the spectral properties and their performance within an acceptable range, i.e., typical customer tolerance of less than 3 DE units in the graphic arts industry.

Color-difference evaluation for 3D objects.

A psychophysical experiment using 3D printed samples was conducted to investigate the change of perceived color differences caused by two different illuminations and two 3D sample shapes. 150 pairs of 3D printed samples around five CIE color centers [Color Res. Appl. 20, 399-403, 1995], consisting of 75 pairs of spherical samples and 75 pairs of flat samples, with a wide range of color differences covering from small to large magnitude, were printed by an Mcor Iris paper-based 3D color printer. Each pair was assessed twice by a panel of 10 observers using a gray-scale psychophysical method in a spectral tunable LED viewing cabinet with two types of light sources: diffuse lighting with and without an additional overhead spotlight. The experimental results confirmed that the lighting conditions had more effect on the perceived color difference between complex 3D shapes than between 2D objects. The results for 3D and 2D objects were more similar under only diffuse lighting. Current 3D results had good correlations with previous ones [Color Res. Appl. 24, 356-368, 1999; J. Opt. Soc. Am. A 36, 789-799, 2019] using 2D samples with large color differences, meaning that color-difference magnitude had more effect on perceived color differences than sample shape and lighting. Considering ten modern color-difference formulas, the best predictions of the current experimental data were found for CAM02-LCD formula [Color Res. Appl. 31, 320-330, 2006]. For current results, it was also found that predictions of current color-difference formulas were below average inter-observer variability, and remarkable improvements were found by adding power corrections [Opt. Express 23, 597-610, 2015].

Skin coloration is a culturally-specific cue for attractiveness, healthiness, and youthfulness in observers of Chinese and western European descent.

Facial skin coloration signals information about an individual and plays an important role in social interactions and mate choice, due its putative association with health, attractiveness, and age. Whether skin coloration as an evolutionary significant cue is universal or specific to a particular culture is unclear and current evidence on the universality of skin color as a cue to health and attractiveness are equivocal. The current study used 80 calibrated, high-resolution, non-manipulated images of real human faces, either of Chinese or western European descent, which were rated in terms of attractiveness, healthiness, and perceived age by 44 observers, 22 western European (13 male; mean age ± SD = 24.27 ± 5.30) and 22 Chinese (7 male; mean age ± SD = 26.05 ± 3.96) observers. To elucidate the associations between skin coloration and these perceptual ratings and whether these associations are modulated by observer or image ethnicity, a linear mixed-effect model was setup with skin lightness (L*; CIELAB), redness (a*) and yellowness (b*), observer and image ethnicity as independent variables and perceived attractiveness, healthiness, and estimated age as dependent variables. We found robust positive associations between facial skin lightness (L*) and attractiveness, healthiness, and youthfulness, but only when Chinese observers judge facial images of their own ethnicity. Observers of European descent, on the other hand, associated an increase in yellowness(b*) with greater attractiveness and healthiness in Chinese facial images. We find no evidence that facial redness is positively associated with these attributes; instead, an increase in redness (a*) is associated with an increase in the estimated age of European facial images. We conclude that observers of both ethnicities make use of skin color and lightness to rate attractiveness, healthiness, and perceived age, but to a lesser degree than previously thought. Furthermore, these coloration cues are not universal and are utilized differently within the Chinese and western European ethnic groups. Our study adds to the growing body of work demonstrating the importance of skin color manipulations within an evolutionary meaningful parameter space, ideally using realistic skin models based on physical parameters.

A colorimetric comparison of sunless with natural skin tan.

The main ingredient of sunless tanning products is dihydroxyacetone (DHA). DHA reacts with the protein and amino acid composition in the surface layers of the skin, producing melanoidins, which changes the skin colour, imitating natural skin tan caused by melanin. The purpose of this study was to characterise DHA-induced skin colour changes and to test whether we can predict the outcome of DHA application on skin tone changes. To assess the DHA-induced skin colour shift quantitatively, colorimetric and spectral measurements of the inner forearm were obtained before, four hours and 24 hours after application of a 7.5% concentration DHA gel in the experimental group (n = 100). In a control group (n = 60), the same measurements were obtained on both the inner forearm (infrequently sun-exposed) and the outer forearm (frequently sun-exposed); the difference between these two areas was defined as the naturally occurring tan. Skin colour shifts caused by DHA tanning and by natural tanning were compared in terms of lightness (L*), redness (a*) and yellowness (b*) in the standard CIELAB colour space. Naturalness of the DHA-induced skin tan was evaluated by comparing the trajectory of the chromaticity distribution in (L*, b*) space with that of naturally occurring tan. Twenty-four hours after DHA application, approximately 20% of the skin colour samples became excessively yellow, with chromaticities outside the natural range in (L*, b*) space. A principal component analysis was used to characterise the tanning pathway. Skin colour shifts induced by DHA were predicted by a multiple regression on the chromaticities and the skin properties. The model explained up to 49% of variance in colorimetric components with a median error of less than 2 ΔE. We conclude that the control of both the magnitude and the direction of the colour shift is a critical factor to achieve a natural appearance.

Investigating unique hues at different chroma levels with a smaller hue angle step.

Unique hue plays a critical role in color appearance models and uniform color spaces. Past studies investigating unique hues commonly used 40 Munsell samples with the same chroma and lightness levels to produce color stimuli, with a hue angle step of 9°. These 40 samples were always simultaneously presented to the observers. Both the larger hue angle step and the simultaneous presentation of the samples may help to reduce the variations. In this study, we reduced the hue angle step to 5° and each stimulus was individually presented to the observer, which resulted in larger inter- and intra-observer variations. The results suggested that the hue angles of the unique hues in both CIECAM02 and CIELAB should be revised, but both CIECAM02 and CIELAB had good hue uniformity at the hue angles of the four unique hues.

"Fake Tan" or "Fake News"?

We estimated Trump's skin colour from 70 internet images and also from the "twitter tan line" image (February 8, 2020; Twitter). We then compared the estimated skin colours with two existing data sets of skin colours: the range of skin tans that occur naturally in the Caucasian population and the range skin colours brought about by a sunless tan. We find that Trump's skin colour is close to the edge of the natural skin tan gamut and firmly within the gamut of a sunless skin tan. The skin colour above Trump's tan line is outside of the naturally occurring range of skin colours, even outside the skin tan of nonmelanized albinos. The latter finding is consistent with the hypothesis that part of the image may have been digitally distorted.

Spectra estimation from raw camera responses based on adaptive local-weighted linear regression.

An improved spectral reflectance estimation method is developed to transform raw camera RGB responses to spectral reflectance. The novelty of our method is to apply a local weighted linear regression model for spectral reflectance estimation and construct the weighting matrix using a Gaussian function in CIELAB uniform color space. The proposed method was tested using both a standard color chart and a set of textile samples, with a digital RGB camera and by ten times ten-fold cross-validation. The results demonstrate that our method gives the best accuracy in estimating both the spectral reflectance and the colorimetric values in comparison with existing methods.

Chromatic and luminance sensitivity for skin and skinlike textures.

Despite the importance of the appearance of human skin for theoretical and practical purposes, little is known about visual sensitivity to subtle skin-tone changes, and whether the human visual system is indeed optimized to discern skin-color changes that confer some evolutionary advantage. Here, we report discrimination thresholds in a three-dimensional chromatic-luminance color space for natural skin and skinlike textures, and compare these to thresholds for uniform stimuli of the same mean color. We find no evidence that discrimination performance is superior along evolutionarily relevant color directions. Instead, discriminability is primarily determined by the prevailing illumination, and discrimination ellipses are aligned with the daylight locus. More specifically, the area and orientation of discrimination ellipses are governed by the chromatic distance between the stimulus and the illumination. Since this is true for both uniform and textured stimuli, it is likely to be driven by adaptation to mean stimulus color. Natural skin texture itself does not confer any advantage for discrimination performance. Furthermore, we find that discrimination boundaries for skin, skinlike, and scrambled skin stimuli are consistently larger than those for uniform stimuli, suggesting a possible adaptation to higher order color statistics of skin. This is in line with findings by Hansen, Giesel, and Gegenfurtner (2008) for other natural stimuli (fruit and vegetables). Human observers are also more sensitive to skin-color changes under simulated daylight as opposed to fluorescent light. The reduced sensitivity is driven by a decline in sensitivity along the luminance axis, which is qualitatively consistent with predictions from a Von Kries adaptation model.