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Best Colors - Fashion Science app for iPhone and iPad


4.6 ( 6496 ratings )
Lifestyle Health & Fitness
Developer: Audibilities, LLC
Free
Current version: 1.0, last update: 6 years ago
First release : 10 Mar 2018
App size: 15.97 Mb

Your best colors from a selfie - Fashion Science!

Based on your colors - who you are - we determine the colors that are good for you - or bad for you. We use a selfie to determine your key colors - from your skin, your hair, and your eyes. Using Fashion Science we then build your personalized color wheel - showing what colors work best for you.

Fashion Science

The goal is to identify the color of clothes that match best to you. With the right colors the claim is this makes you more attractive than wearing neutral or bad colors.

Historically the approach taken is seasonal colors, as illustrated by the popular book in the 1970s Color Me Beautiful. This segments humans into four seasons - winter, spring, summer and fall - each season having specific colors that are appropriate for people in that season. Further refinement has taken the four seasons approach into more segments, still based on seasonality - 12 and 16 segments are common.

From our experimental data testing this approach - we have analyzed well over 100,000 selfies from a global sample - it just doesnt hold water that people segment this way. It turns out that humans range over this space in a continuous fashion rather than supporting a statistical bucketing. And anecdotally this was confirmed - "oh, Im not really a Spring - in some cases Im a Summer", ...

Our approach - Personalization based on You

We define the physical you as your selfie - from which we identify your skin, hair, and eyes. Those colors define the current you. At that point we use color harmonies to determine the range of colors that work with you. These color harmonies include:
+ monochromatic
+ complementary
+ analogous.
All harmonies are based on the source colors. All colors in the color wheel can be traced back to the selfie.

This works great in a perfect world, with perfect lighting, high quality cameras and color correction approaches such as a gray card. Unfortunately that isnt the normal world we live in.

Key issues weve seen, in well over 100,000 selfies so far include:
- Poor lighting, generally too dark
- Shadows from bright lighting, e.g., hiding the eyes
- Other poor composition including bright backgrounds that blend into the hair, and others
- Unknown errors generated by the smart phone camera image processing system (e.g., focusing on something other than the face for a selfie.)

An approach discovered here is a method to dynamically determine the appropriate adjustments on a selfie to bring colors back to the real world. This is an AI algorithm (using a CNN) that is patent pending.

Note that evaluating a real world image, e.g., a store against a personalized color wheel involves using a non-corrected image. This is a problem. Currently we expand the error bars for matching, i.e., allowing more permissable colors.

Evaluating colors against a catalog, where the colors are explicit and correct works very well.

Common Questions

+ What about bright yellow for me? (or Green, Blue, etc.) Go for it. By its nature this approach (currently) wont find bright colors for you outside of your source colors (monochromatic harmony) - your source colors are generally low in saturation - or close to the center of the color wheel. This is an open topic of research.

+ What about highlights in my hair? Colored contacts? Strong make-up? These colorations are used to define you, so your color wheel - your preferred colors will reflect the new you.

+ What about patterns in fabric? Patterns in fabrics are designed so that the individual colors work well together. Your color wheel will usually support all or none of the colors. If a partial match is seen, that is part of the pattern is good, part bad we have to go with the science and say that the pattern is bad for you.

Collaboration and Research

Collaborators are invited. There are many areas to be explored, ranging from the technical (code/hosting) to AI to fashion science and applicability.