Face Recognition Device

This advanced face recognition device automates time registration using face recognition. It also seamlessly integrates with third-party extensions and running apps on a PC, binding them with individuals and generating reports.

Challenges

Hardware Limitations: Implementing face recognition with limited hardware resources.
Cluster Selection: Choosing the right cluster for optimal face recognition performance.
Accuracy and Speed: Ensuring fast and accurate recognition for precise time tracking.
Performance and Scalability: Maintaining responsiveness and stability under high loads.
Multiple Face Detection: Supporting simultaneous recognition of multiple faces.
Application Usage Monitoring: Accurately tracking time spent on different applications.

Our Approach

We adopted a modular approach, dividing the project into sub-projects for efficient development: back-end, front-end, and desktop listener. The team has created a platform compatible with both desktop PCs (using standard USB cameras) and resource-constrained Linux platforms (like Raspberry Pi). The system operates asynchronously, processing captured images in the background to maintain optimal performance.

Services Provided

Mechanical EngineeringFirmware DevelopmentSoftware DevelopmentMachine LearningBack-End DevelopmentDeep Neural NetworkingWeb Application DevelopmentUI/UX Design

Key Features

User registration and management.
Confirmation and merging of recognition results for improved accuracy.
Wi-Fi access to the dashboard.
Detailed reporting.
Possibility to extend desktop applications.

Results

We've managed to create a highly responsive, social-network-like app that provides users with a completely new experience and operates flawlessly on both Android and iOS. Our solution has proven stable and suitable for use as an automated logging system and increased efficiency of time tracking for the client.

Achieved recognition accuracy - 98%

Achieved recognition speed - 10 fps

Optimized device size for workstations.

Technologies Used

Other

C/C++GoVueJSRaspberry Pi

What Our Team Says

Yaroslav

Backend Software Developer

I enjoyed working on new product development because you can see the tangible results of your work and even hold the device in your hands. Developing face recognition technology for this device was a complex but rewarding challenge.

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