FACIAL MAPS TESTING
that shows microbiome dynamics by highlighting shifts in relative abundance of one species versus another[4]
.
From a technical point of view, we initially defined 30 distinct measurement sites on one half of the face (figure 1a). These 30 sites serve as a template for mapping but can be customised depending on the need. For example, we mapped the skin microbiome at five specific sites[4]
.
TEXTURED FACIAL MAPS FOR CLAIM
V
isualising the treatment effects of skin care actives is an important aspect of claim substantiation and promotion
of these ingredients. To this end, we developed facial colour mapping, an award-winning approach to visualising complex scientific data in an easy-to- understand way. With an eye to the next generation of mapping approaches, we present our proposal for a textured facial map. This type of facial map offers new opportunities for claim substantiation for cosmetic applications.
SIMPLIFYING SCIENTIFIC CONTENT Scientific content is often perceived as difficult to understand for consumers and people who are unfamiliar with a specific topic of interest. It is therefore essential to convert scientific evidence into a consumer-friendly and easily understandable form. Visualisation offers considerable potential because images are usually well perceived by humans and information
cosmeticsbusiness.com
A typical facial colour map displays an interpolated gradient of defined colours assigned to data for each measurement site. In the case of facial hydration mapping, we chose a red to white to blue gradient representing red for dry skin, white for normal skin and blue for hydrated skin (figure 1b).
TEXTURED FACIAL MAP
SUBSTANTIATION To visualise the treatment effects of skin care actives, DSM Nutritional Products developed textured facial mapping, as Remo Campiche, Thibault Vergne, Marie Cherel, Mathias Gempeler and Ghislain François explain
displayed as an image is captured faster. To address the need for
understandable scientific data display, we developed and introduced continuous facial colour mapping, initially to display skin hydration data and measurements of transepidermal water loss[1]
. We then extended this technology
further, to maps displaying facial sebum content or statistical significance values[2,3]
.
Our most recent innovation in this area was the creation of a facial map
Based on the original facial colour map approach for skin hydration, we aimed to extend this type of mapping beyond colour gradients.
One of the biggest challenges is how to reproduce the look of dry skin and its transformation to well hydrated skin in a more natural way without losing the apparently powerful way of mapping hydration with a colour gradient. We took inspiration from the fact that dry skin shows white areas, so-called scales, due to increased desquamation which makes dry skin feel rougher than hydrated skin. Along those lines we overlaid a mesh or a grid on the image of an average face.
Initial trials involved meshes based on Delaunay triangulation and Voronoï cells[5]
. The Voronoï type of cells was chosen to create a mesh in white colour because we felt it was the better fit visually, mainly due to the lack of dots at the intersections of the mesh edges. The edges of the mesh were adapted by slightly bending them to mimic scaly skin (figure 2).
A gradient was applied in the same way as for the colour maps but, this time,
Figure 1 a) The 30 pre-defined measurement sites on the face. b) A continuous facial colour map with a gradient showing dry (red) to well hydrated (blue) skin on a caucasian, black African and Indian face (from left to right)[1,2]
.
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