Face Recognition Device
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.
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.
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.
RESULTS
WHAT OUR TEAM SAYS
about the project
WHAT OUR TEAM SAYS
about the project
target audience
This face recognition device is particularly valuable for remote teams or businesses with flexible work arrangements that need employee monitoring solution. *It's important to remember though that each employee must consent to the use of this device.
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