Moscow

VisionLabs

Face DJ is based on 3D face model reconstruction technology and can transfer it to virtual reality. 3D model reconstruction from a single Image is available due to the technology that defines key points on the face and transfers them to the adaptable virtual head model.

Individual face features are defined in the image, and the virtual model adapts to them. Face key points definition algorithm includes 2 stages. Firstly, the face is detected in the image, then it is extracted from the image and complemented with a set of pre-defined key points. Machine learning is used in both stages. 

<a href="https://itunes.apple.com/ru/app/face-dj/id1208394008?mt=8" target=«_blank">Mobile app</a>

App for 3D model creation and transferring images to virtual reality

recognition

artificial_intelligence

machine_learning

Face.DJ

Luna Platform is based on LUNA SDK - Engine for face recognition. The system includes several modules: Broker web server, which ensures interface with external systems via HTTP protocol; Extracto handler, which extracts face descriptors; Matcher handler, which receives requests for descriptors matching. An additional Queue Manager ensures data exchange between Broker module and Extractor and Matcher handlers. DBMS Aerospike NoSQL module is used to create a storage for descriptors and their lists. The modules work independently from each other. The system uses RESTful Web API to transmit commands and exchange data.

 The main Application level protocol is HTTP 1.1, data exchange is initiated by an HTTP request. The implementation of neural networks allows to process a face in a fraction of a second, and the optimized sublinear search makes it possible to identify a person in the databases. The descriptors data is de-identified

System of data management and person verification and indentification

computer_vision

neural_networks

biometry

LUNA Platform

Specialized software for checking and identifying people, it ensures accurate facial recognition in images and also in video streams in real time.

Facial recognition processing in LUNA SDK includes several modules: face detection, face alignment in the images, face descriptors extraction, matching of the faces with image database, defining face attributes and prevention of face spoofing.

The system was developed in C++ and allows to optimize memory management, work in extensive multithreading mode, the system ensures high efficiency of the modules, allows to carry out cross-platform integration and use standard API in C++.

LUNA SDK uses deep neural networks (DNN) for face detection and descriptors extraction.

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LUNA SDK

Luna makes it possible to open a car without keys and operates as a plug-in on the Nvidia Drive IX platforms run on Nvidia Drive AGX supercomputer. The service is based on the data control and is used for verification and recognition of the Luna SDK users’ faces.

It uses the caroms both inside and outside of the car. When the user approaches the vehicle, the system scans his face. Then it compares the collected data with the previously registered data. If the system finds a match, the doors will be unlocked.

Service providing face recognition forcer access

transportation

Luna for cars

The service helps job candidates do their preliminary interview as successfully as possible. To get the service, the user needs to download a video file with self-presentation where he will tell what he’s going to say during the interview.

Then the neural network from Russian startup VisionLabs processes the files and gives its evaluation on the basis of the poll of 537 HR specialists from different industries of business. According to the developers, the neural network has already been trained on more than 1000 video files with self-presentations and learned how to calculate the probability of a successful interview.

The expert proceeds to view the record and points out the mistakes in the presentation. The neural network and expert evaluate what the candidate is saying, his intonation, speech speed and loudness, as well as gestures, pose and mimics. As a result, the user receives a written report (example) on the probability of successfully passing the interview and the results on every evaluated factor.

AI-based service for individual preparation for negotiations

personnel

HR-Tech

Success interview formula

SWiP application allows to pay for purchases using selfies using Selfie2Pay payment solution. After downloading the application and linking the bank card, the application asks the user to take a photo. Face biometric data is used for payment. Cameras installed at sales outlets read biometric parameters of the client’s face (creates a 3D model of the customer's face). To confirm the payment the client needs to look into the camera.

<a href="https://play.google.com/store/apps/details?id=com.it.swip" target="«_blank&quot;">Mobile app</a>

Tech Solutions

Face.DJ

LUNA Platform

LUNA SDK

Luna for cars

Success interview formula

SWiP