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Unik plug-and-play løsning til 3D ansigtsgenkendelse

Unik plug-and-play løsning til 3D ansigtsgenkendelse

ams og MEGVII vil i fællesskab udvikle en komplet løsning til 3D ansigtsgenkendelse, der let kan integreres i en bred vifte af produkter, og som efter planen vil blive tilgængelig i slutningen af året (in english).

ams, a leading worldwide supplier of high performance sensor solutions, and artificial intelligence pioneer MEGVII today announce they have signed a partnership agreement to jointly develop and promote complete, plug-and-play 3D face recognition solutions for any type of smart consumer or commercial device.

Under the new memorandum of understanding, the two companies expect to offer the world’s first off-the-shelf face recognition system for smart home, smart retail, smart building and smart security applications, completely independent of the user’s mobile phone.


Mobile phone users have rapidly adopted face recognition as their preferred means of user authentication, especially for security reasons. Manufacturers of other types of products are now keen to gain the convenience and security benefits of implementing face recognition. ams and MEGVII plan to bring their joint solution to market before the end of 2019.

Applications and benefits

The integrated solution under development combines ams’ proven Vertical-Cavity Surface-Emitting Laser (VCSEL) emitter modules with MEGVII’s software for depth mapping and face recognition. As a result, the two companies will create the first 3D Active Stereo solution with very robust performance in both indoor and outdoor light conditions. In addition, the solution will meet very high security standards: for instance, it will be suitable for use in consumer payments systems such as point-of-sale terminals.

MEGVII and ams have combined successfully before to develop a complete face recognition solution for mobile phones. The new solution, which will be compatible with a much wider range of applications processors from various manufacturers, will greatly reduce the development time, risk and effort involved in implementing face recognition in embedded systems such as smart locks, access control equipment and payment terminals.

4/7 2019
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