Real-Time Facial Recognition Software Powered by AI
How Does Facial Recognition Technology work?
Facial recognition uses computer algorithms to examine facial characteristics. It performs biometric identification by picking up distinctive features on a person’s face.
The technology transforms analog information (a face) into digital data based on the facial features.
We can divide the facial recognition into three stages: face detection, face capture, and face match.
Businesses deploy different systems for facial recognition. They vary depending on their error rate and ability to capture the data under challenging conditions, such as low-quality photos, poor lighting, and angle of view.
Open-Source Scrips For Facial Recognition vs Customized Solutions.
Open-source scripts that currently exist do not work in real scenarios. They are questionable from data protection and data security point of view.
Customized solutions adapt to your business’ needs and comply with applicable legislation.
Start Using Facial Recognition Technology in Your Business To
Cut costs of producing tickets and keys. In hotels, facial recognition can replace keycards, for airlines - boarding passes, for events - event tickets. Facial recognition can speed up the checkpoint process and offer a seamless experience without the inconvenience of carrying passes or keys.
Drive sales and marketing ROI by personalizing the customer experience with real-time audience analysis. Detect facial expressions to analyze customer’s paths in stores, track cart items, and offer product recommendations.
Automate payments, save time and cost of manual labor. Use face recognition technology for seamless contactless payments, quicker access to ATMs, and faster self-checkouts.
Facial Recognition Solutions by BroutonLab.
Our Data Scientists use advanced techniques of deep learning and computer vision. We achieve high accuracy of face recognition that tackles a variety of business problems.
We trained a deep siamese neural network to achieve lightning-quick identification of a person. We designed an SDK to deliver maximum performance regardless of input, with an error rate close to 0.
The neural network, trained in Tensorflow, detects vehicles, plate numbers, and letters with digits.
Our models are integrated into an optimized, multithreaded C++ agent. It communicates with the server via GRPC protocol. The cross-platform works on Windows, Mac, and Linux. It collects, stores, and monitors data from various camera types.
Key Features of Our Face Recognition Technology
Fast one-shot facial recognition
Fake face detection (works for mobile screens and printed photos)
High accuracy and security (no false positives)
Optimized models via SDK for C ++, C#, and Java
Solution that w orks independently with no internet access.