Inspiration
Facial recognition is a way of identifying or confirming an individual's identity using their face. Facial recognition systems can be used to identify people in photos, videos, or in real-time. Facial recognition is a category of biometric security.
What it does
Facial recognition is used when issuing identity documents and, most often, combined with other biometric technologies such as fingerprints (preventing ID fraud and identity theft). Face match is used at border checks to compare the portrait on a digitized biometric passport with the holder's face
How we built it
Face recognition systems use computer algorithms to pick out specific, distinctive details about a person's face. These details, such as distance between the eyes or shape of the chin, are then converted into a mathematical representation and compared to data on other faces collected in a face recognition database.
Challenges we ran into
It requires proper techniques for face detection and recognition with challenges of different facial expressions, pose variations, occlusion, aging and resolution either in the frame of stationary object or video sequencing images
Accomplishments that we're proud of
The most significant impacts and benefits are: Time Savings and Better Productivity—Medical professionals normally spend a large percentage of their day doing paperwork. That's where speech recognition technologies can have an impact. It takes time to write or type out notes, but it is quicker to speak them aloud.
What we learned
A facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match. Facial recognition can help verify a person's identity, but it also raises privacy issues.
What's next for Face Recognition System
How will facial recognition be used in the future? Facial recognition solutions are expected to be present in 1.3 billion devices by 2024. Powered by AI, facial recognition software in mobile phones is already being used by companies like iProov and Mastercard to authenticate payments and other high-end authentication tasks
Built With
- machine-learning
- python
- vs-code
Log in or sign up for Devpost to join the conversation.