The best verification algorithm in the world. Proven by the latest independent testing of face recognition engines.
Winner of the Intelligence Advanced Research Projects Activity (IARPA) Face Recognition Prize Challenge (FRPC). See the report below and a detailed report on nist.gov.
|IARPA FRPC||Wild (FMR=0.001 ?)|
|2||XXX algorithm||0.35 (-59%)|
|...10||YYY algorithm||0.68 (-209%)|
At the recent Face Recognition Vendor Test, conducted by the National Institute of Standards and Technology (NIST), NtechLab’s face recognition technology showed the best performance on sophisticated datasets – “wild” and “child” – among all participants for large-scale verification.
|NIST FRVT||Wild (FMR=0.0001)||Child (FMR=0.01)|
|2||XXX algorithm||0.344 (-27%)||0.549 (-27%)|
|...10||YYY algorithm||0.508 (-87%)||0.631 (-46%)|
The IARPA Face Recognition Prize Challenge found NtechLab to have the world’s fastest algorithm. It is currently the world’s only algorithm with sub-linear search time.
NtechLab’s algorithm works on planetary scale datasets with billions of faces, showing the best accuracy and speed performance:
Search time on huge datasets:
Our face detection algorithm is renowned for revolutionary speed and accuracy. In a single shot our algorithm processes an unlimited number of faces, perfectly tailored for mass events. It is resistant to lighting conditions, posture, head poses and tilts.
Detects a person’s age with 95% accuracy in 5 years’ intervals.
Detects a person’s gender with 99% accuracy.
Age and gender detection can be adopted across a wide range of use cases and markets including targeted offline advertisement, access control and data enrichment.
Detects 7 primary and 50 compound emotions of a person. Captures and interprets emotional data to deliver actionable insights.
Emotion detection can be adopted across a wide range of use cases and markets including entertainment and media, client satisfaction measurement.
Algorithm’s quality is proven by 1st place at EmotioNet Challenge 2017.
Powered by Ntechlab face recognition algorithm, FindFace Enterprise Server SDK effectively processes face recognition and works on the client’s side – no biometric data is transferred or stored by NtechLab. It detects and identifies people’s faces in live video streams and video footage addressing a wide range of business tasks, such as precise people count, demographic information, people flow and client behavior. FindFace Enterprise Server SDK allows for integration into any web, mobile, or desktop application using cross-platform REST API.
FindFace Enterprise Server SDK 2.0 can be adopted across a wide range of use cases and industries including customer analytics, client verification, fraud prevention, hospitality, and access control. It can be deployed across retail, banking, entertainment, sports, event management, dating services, security, public safety, homeland security, and more.Learn more
FindFace Cloud leverages the industry’s fastest face recognition technology to bring you the speed, accuracy, scalability and cost advantages. Our intuitive, cross-platform REST API allows for a fast and seamless integration into any custom application or service. FindFace Cloud offers a completely secure environment purpose-built for offsite data storage and management.Learn more
Powered by Ntechlab face recognition algorithm, FindFace Security accurately recognizes faces and runs on the client’s side – no biometric data is transferred or stored by NtechLab. It detects and identifies people in images and live video streams, creating an extra level of security for law enforcement and business organizations. Our solution can be used for access control, fraud and theft prevention, accelerating the investigation of the embezzlement of data and physical assets in a timely manner.
The solution also helps increase customer loyalty and satisfaction through personalized recommendations and anonymous analysis of shoppers’ behavior. FindFace Security can be used in a wide range of areas such as retail, banking and finance, sporting and other mass events, corporate and public safety.Learn more
Facial recognition algorithms analyze photographic images for the characteristics visible to an untrained eye. We can determine with good accuracy age, gender and certain emotions, as well as if the person is wearing sunglasses or a mustache. Those classifiers may have practical applications in retail, healthcare, entertainment and other industries by delivering accurate and timely demographic data to enhance the quality of service. Thus the algorithm has the ability to confirm the accuracy of manually entered demographic records, or to narrow the database search.