Daily consumption of a fruit and vegetable smoothie alters facial skin color

Consumption of dietary carotenoids or carotenoid supplements can alter the color (yellowness) of human skin through increased carotenoid deposition in the skin. As fruit and vegetables are the main dietary sources of carotenoids, skin yellowness may be a function of regular fruit and vegetable consumption. However, most previous studies have used tablets or capsules to supplement carotenoid intake, and less is known of the impact of increased fruit and vegetable consumption on skin color. Here, we examined skin color changes in an Asian population (Malaysian Chinese ethnicity) over a six week dietary intervention with a carotenoid-rich fruit smoothie. Eighty one university students (34 males, 47 females; mean age 20.48) were assigned randomly to consuming either a fruit smoothie (intervention group) or mineral water (control group) daily for six weeks. Participants’ skin yellowness (CIELab b*), redness (a*) and luminance (L*) were measured at baseline, twice during the intervention period and at a two-week follow-up, using a handheld reflectance spectrophotometer. Results showed a large increment in skin yellowness (p<0.001) and slight increment in skin redness (p<0.001) after 4 weeks of intervention for participants in the intervention group. Skin yellowness and skin redness remained elevated at the two week follow up measurement. In conclusion, intervention with a carotenoid-rich fruit smoothie is associated with increased skin redness and yellowness in an Asian population. Changes in the reflectance spectrum of the skin suggest that this color change was caused by carotenoid deposition in the skin

Facial Skin Coloration Affects Perceived Health of Human Faces

Numerous researchers have examined the effects of skin condition, including texture and color, on the perception of health, age, and attractiveness in human faces. They have focused on facial color distribution, homogeneity of pigmentation, or skin quality. We here investigate the role of overall skin color in determining perceptions of health from faces by allowing participants to manipulate the skin portions of color-calibrated Caucasian face photographs along CIELab color axes. To enhance healthy appearance, participants increased skin redness (a*), providing additional support for previous findings that skin blood color enhances the healthy appearance of faces. Participants also increased skin yellowness (b*) and lightness (L*), suggesting a role for high carotenoid and low melanin coloration in the healthy appearance of faces. The color preferences described here resemble the red and yellow color cues to health displayed by many species of nonhuman animals

Face colour under varying illumination - analysis and applications

Abstract The colours of objects perceived by a colour camera are dependent on the illumination conditions. For example, when the prevailing illumination condition does not correspond to the one used in the white balancing of the camera, the object colours can change their appearance due to the lack of colour constancy capabilities. Many methods for colour constancy have been suggested but so far their performance has been inadequate. Faces are common and important objects encountered in many applications. Therefore, this thesis is dedicated to studying face colours and their robust use under real world illumination conditions. The main thesis statement is "knowledge about an object's colour, like skin colour changes under different illumination conditions, can be used to develop more robust techniques against illumination changes". Many face databases exist, and in some cases they contain colour images and even videos. However, from the point of view of this thesis these databases have several limitations: unavailability of spectral data related to image acquisition, undefined illumination conditions of the acquisition, and if illumination change is present it often means only change in illumination direction. To overcome these limitations, two databases, a Physics-Based Face Database and a Face Video Database were created. In addition to the images, the Physics-Based Face Database consists of spectral data part including skin reflectances, channel responsivities of the camera and spectral power distribution of the illumination. The images of faces are taken under four known light sources with different white balancing illumination conditions for over 100 persons. In addition to videos, the Face Video Database has spectral reflectances of skin for selected persons and images taken with the same measurement arrangement as in the Physics-Based Face Database. The images and videos are taken with several cameras. The databases were used to gather information about skin chromaticities and to provide test material. The skin RGB from images were converted to different colour spaces and the result showed that the normalized colour coordinate was among the most usable colour spaces for skin chromaticity modelling. None of the colour spaces could eliminate the colour shifts in chromaticity. The obtained chromaticity constraint can be implemented as an adaptive skin colour modelling part of face tracking algorithms, like histogram backprojection or mean shift. The performances of these adaptive algorithms were superior compared to those using a fixed skin colour model or model adaptation based on spatial pixel selection. Of course, there are cases when the colour cue is not enough alone and use of other cues like motion or edge data would improve the result. It was also demonstrated that the skin colour model can be used to segment faces and the segmentation results depend on the background due to the method used. Also an application for colour correction using principal component analysis and a simplified dichromatic reflection model was shown to improve colour quality of seriously clipped images. The results of tracking, segmentation and colour correction experiments using the collected data validate the thesis statement

Designing a simple 3-channel camera for skin detection

Skin detection is an important preprocessing step for many applications. In some cases, reliable detection is needed under the real-world's challenging illumination conditions, that is, when the prevailing illumination does not correspond to the one used in calibration. Our particular goal in this paper is to design and study a three-sensor camera for these kinds of illumination conditions. This is done in three stages. First, a representative set of illuminants is selected from a given color temperature range. In the second stage, different illumination normalization methods are tested for the camera channel model. Simple bell-shaped sensors are tested with a chosen normalization method in the last stage. Different sensor combinations are evaluated based on their gamut ratios for skin and Munsell reflectances

Thermal Behavior of an Asphalt Pavement in the Laboratory and in the Parking Lot

The urban, constructed areas are full of buildings and different kinds of pavements and have a noticeable lack of trees and flora. These areas are accumulating the heat from the Sun, people, vehicles, and constructions. One interesting heat collector is the asphalt pavement. How does the heat transfer to different layers under the pavement or does it? What are the temperatures under the pavement in Finland where the winter can be pretty hard? How can those temperatures be measured accurately? These are the main questions this paper gives the preliminary answers to. First the thermal behavior of asphalt and the layers beneath are researched in the laboratory and then the measurement field is bored and dug in the parking in the Western coast of Finland, 63°5′45′′ N. Distributed temperature sensing method was found to be a good choice for temperature measurements. Thermal behavior of pavement has been monitored in different layers and the preliminary results have been published here. The goal of this research is to assess the applicability of asphalt pavements for heat energy collection

Colour detection thresholds in faces and colour patches

Human facial skin colour reflects individuals’ underlying health (Stephen et al 2011); and enhanced facial skin CIELab b* (yellowness), a* (redness), and L* (lightness) are perceived as healthy (also Stephen et al 2009). Here, we examine Malaysian Chinese participants’ detection thresholds for CIELab L* (lightness), a* (redness), and b* (yellowness) colour changes in Asian, African, and Caucasian faces and skin coloured patches. Twelve face photos and three skin coloured patches were transformed to produce four pairs of images of each individual face and colour patch with different amounts of red, yellow, or lightness, from very subtle (Δ E = 1.2) to quite large differences (Δ E = 9.6). Participants were asked to decide which of sequentially displayed, paired same-face images or colour patches were lighter, redder, or yellower. Changes in facial redness, followed by changes in yellowness, were more easily discriminated than changes in luminance. However, visual sensitivity was not greater for redness and yellowness in nonface stimuli, suggesting red facial skin colour special salience. Participants were also significantly better at recognizing colour differences in own-race (Asian) and Caucasian faces than in African faces, suggesting the existence of cross-race effect in discriminating facial colours. Humans’ colour vision may have been selected for skin colour signalling (Changizi et al 2006), enabling individuals to perceive subtle changes in skin colour, reflecting health and emotional status