Eyewear

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3D scanning in eyewear

Fuel3D specializes in rapid 3D scanning solutions; our technology is at the forefront of innovation and personalization in many sectors, including eyewear.

 

Fuel3D technology for eyewear

In the eyewear sector, we’re at the forefront of very exciting applications such as virtual try-on, custom-fit and personalized manufacturing.

Our 3D scanning platforms are designed around 180°, 270° and (in the future) 360° point-of-sale scanning solutions; capturing accurate 3D geometric data and color in an amazing 0.1 seconds: that’s faster than the blink of an eye.

Here’s how we fit into the eyewear digitization supply chain:
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The measurements you need for customer satisfaction

Poor fitting glasses and misalignment of the lenses with the eyes are two well-known challenges; accurate 3D scanning of the customer’s head and facial features, together with accurate measurement of pupillary distance, are delivered quickly with Fuel3D 3D scanning.

Fuel3D scanning solutions can provide all of the measurements you need:

  1. Head width
  2. Bridge width
  3. Interpupillary distance
  4. Bridge projection
  5. Eye-ear distance
  6. Pantoscopic tilt
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We are ready to build exciting new systems with you:

  • Existing hardware platforms: Our 180° scanners: the in-store mirror scanner, and our super-portable SCANIFY scanner; are ready for deployment now.
  • Software development kit: Our SDK will be ready in 2Q17 to assist customers and developers in partnering with us to develop and build exciting new eyewear applications.
mirror scanner

Fuel3D’s 180° mirror scanner for in-store use

scanify-face

Fuel3D’s 180° SCANIFY scanner for handheld use

Interested or just curious?

If so, here’s the form to find out more:

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Fuel3D Project 2SEVENTYTM

Fuel3D has been awarded funding of € 1.7 million from the European Commission’s Horizon 2020 Research and Innovation Programme to support the development of a 270° 3D scanner that will allow full-face capture from a single 3D scan. Learn more

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

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