NtechLab - Augmenting Intelligence

Our algorithms

Face verification100%

Face recognition for verification

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 ?)
	ALGORITHM	FNMR ?
1	NtechLab	0.22
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)
	ALGORITHM	FNMR	FNMR
1	NtechLab	0.271	0.433
2	XXX algorithm	0.344 (-27%)	0.549 (-27%)
...10	YYY algorithm	0.508 (-87%)	0.631 (-46%)

Face identification

Face recognition for identification

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:

250 million faces in dataset – search time is less than 0.2 sec.
500 million faces – less than 0.3 sec.
1 billion faces – less than 0.5 sec.

Face Detection3 faces found

Face detection algoritms

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.

Аge, Gender28 years, male

Age and gender recognition algorithm

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.

EmotionsАstonishment

Emotion recognition algorithm

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 1^st place at EmotioNet Challenge 2017.

Our products

FindFace Enterprise Server SDK

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.

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FindFace Cloud API

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.

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Coming soon

Tracks the silhouette and path of a person passing by the camera:

Accurate people count

Effective in big crowds
where people obscure each other

Effective coupled with face recognition
or as a stand-alone

Recognizes a person’s ethnicity

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.