20face is a spin-off from the University of Twente and is a fast-growing scale-up that offers biometric recognition in a privacy-proof system. Biometric recognition is a key enabling technology that is certainly becoming mainstream.
20face has built an ecosystem of self enrollment, consent and personal data release management (PDRM) around the core technology of biometric recognition.
20face has added privacy by design to biometric recognition to remove a number of important dissatisfiers: User acceptance, Business acceptance and privacy infringements.
Our Privacy Proof biometrics Ecosystem is now available for custom built solutions.
We have a system of algorithms that is patent pending and allows for optimised recognition in uncontrolled environments. We can handle over 60 degrees pose variations, recognise resolutions from 30×30 pixels, works with extreme lighting conditions and we can recognise people by only a partial image of the face. We are now applying our technology in custom built solutions.
Our software product is designed to allow for easy integration in a variety of applications. We offer it for a very affordable licence fee and a shared revenue model. Our main focus is upscaling our technology through the use of an existing platform technology.
If you have any questions or need any advice on our technology please contact us.
An accurate and fast facial recognition software technology is indeed one of the most promising enabler technology of the future, from smart-homes and automobiles to safe and secure societies, face recognition is playing and will continue to play its crucial role. At 20Face we are keenly interested in deploying our 20Face facial recognition technology to build innovative solutions and solve real-world problems
Robust and accurate facial landmarking (such as eyes, eye brows, nose tip, cheek and chin line, etc.) is one of the key part of the 20Face facial recognition technology. This part of our software is customized and commercialized for face analysis in combination with a database that can score faces.
At the Heracles football stadium, 20Face is carrying out a pilot for access-control and hospitality system using facial recognition technology. The goal of the project is to build facial recognition based ticketing, access-control and hospitality services at the VIP seating areas of the stadium.
20face has built an ecosystem of self enrollment, consent and personal data release management (PDRM) around the core technology of biometric recognition
Self enrollment: users puts themself in the system through an app. A photo is taken in the app and uploaded, after which 20face distils the face vectors and encrypts it in a hash (an array of numbers that cannot be reverse engineered), after which the photo is deleted. These vectors are used for recognition.
Consent: a user always gives permission to be recognized by an endpoint (a camera or group of cameras for example in a company). If the user does not give permission (consent), the person will not be recognized.
Personal data release management (PDRM): The user has a personal safe in which he or she secures the personal data. During recognition, the data, that the user has entered himself and that the user consciously gives permission for the recognizing side to use, is released. For access management, for example, this will be the first and last name, but it can also be the age, for example, when purchasing alcohol or tobacco.
Because our technology is extremely scalable we could make our product work for millions of people in different applications.
All these faces are stored in the cloud and can be called up immediately for instant recognition. That takes milliseconds. In addition, everything in the cloud is encrypted and stored decentralised. We use Distributed Ledger Technology for this, which is also known as the underlying technology for the blockchain. This makes it virtually impossible to obtain facial data or contextual data (where was someone at a certain time etc) from users. In fact, only the users can do that themselves.
Our team consists of experienced researchers in the field of facial recognition and enthusiastic software engineers who are keenly interested in translating state-of-the-art face recognition research results into practical solutions to solve real-world problems in the best possible ways.