Introducing FitsYou

PERFECTLY MEASURED 3D FITTING


Our innovative 3D capture and fitting platform empowers opticians and retailers to provide a superior personalised service through best-fit recommendations and fully customised eyewear, online and in-store.



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A new dimension in
frame recommendation

FitAdvisor provides a unique combination of fast 3D face analysis, measurement and AI frame recommendation.

Enhancing the customer experience by offering customers the chance to view their recommended frame style in Augmented Reality. Online and high-street stores have the ability to drive repeat sales through recommending suitable frames from the stores inventories.

Fast 3D capture

Provided through an app store app, we are able to rapidly capture high resolution 3D depth and RGB image data to provide fast analysis of a users face.

Delivering a unique and innovative way to truly understand each customers face.

Accurate facial analysis

With a 270 degree 3D geometry of each customer's face, we are able to provide live in-camera measurements of face height, face width, PD, near PD, bridge, temple to ear and face shape.

Creating a unique fitprofile

Using a unique AI recommendation engine, our system combines key fitting metrics with user and store preferences to provide a personalised recommendation of frame, size, shape, colour and even brand.

This simplifies the customer's choice and allows them to find their perfect pair.

Scaled AR try on

Once the recommendation has been given, FitAdvisor is able to provide customers with an Augmented Reality viewing experience, allowing them to fully understand how the recommended frames will look on them.

Scaled AR try on replicates the exact size of each frame to provide realistic style and fit. This is set to revolutionise customer experience by enabling store advisors to guide customers more effectively.

A revolution in fit

Combining cutting edge 3D reconstruction with best fit AI recommendation and parametric model fitting, RealFit Custom takes the FitAdvisor app as a base to produce personal best fit recommendations or a full custom pair of frames.

This provides eyewear brands and retailers a unique competitive advantage. Improving the fit, form and function of frames, bringing innovation and standout to the customer experience.

Live Measure Capture App

Available through an app store app, we are able to rapidly capture high resolution 3D depth and RGB image data with sub-millimetre accuracy, reconstructing this to generate and display an optimised model of each customer's face.

This offers customers a completely new way to explore how frames sit, feel and look on their face.

Creating a unique fitprofile

Using a unique AI recommendation engine, our system combines key fitting metrics with user and store preferences to provide a personalised recommendation of frame, size, shape, colour and even brand.

This simplifies the customer's choice and allows them to find their perfect pair.

Accurate 3D frame fitting

Utilising 3D models of frames, RealFit Custom provides optimised best fit recommendations of an existing frame inventory.

By utilising our parametric engine to automatically adjust key frame properties, custom frames can be created for each customer. Even the frame colour and lens type can be adjusted and viewed, delivering a completely new product experience.

MANAGED BEST FIT FRAME FULFILMENT

With easy integration, the RealFit Custom system can manage frame orders, fulfilment options to home or store alongside key customer information. This makes attribution and tracking system performance fully transparent.

Fully customised frame output

Frame models can be output for 3D print or as optimised CAD models for traditional manufacturing. Users can even choose to add their own personal touches to the frame, marking out a RealFit Custom experience from any other.

REGISTER YOUR INTEREST AND GET A COPY OF OUR REPORT LOOKING AT THE IMPACT OF FIT ON THE BUYER EXPERIENCE


*This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 710384