Facial recognition systems are automated technologies that can identify or verify a person's identity using their facial features. These systems use algorithms and machine learning to analyze and compare facial images with a database of known faces to determine if there is a match.
- A Review of Face Recognition Technology
- Design and Implementation of a Real-Time Face Recognition System Based on Artificial Intelligence Techniques
This solution provides the following:
- Face recognition accuracy 99.38%
- Ability to identify multiple people at once in real time based on one or more reference images.
- Ability to track and assign a unique identifier to each person in the camera image or video.
- Ability to return a similarity measured between detected faces and reference faces.
Can be used in access control systems or Online Proctoring systems for student authentication or bank authentication
Input 1 (video or image to process, capable of processing):
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mjpeg stream
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rtsp stream
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USB camera devices
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video files (avi, mp4, mkv formats supported)
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standalone image files (.png, .jpg formats supported)
Input 2:
Reference images to which the system compares the faces in the image. (.png, .jpg formats supported)
Outputs:
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Processed video frame
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The faces in the frame (bounding boxes)
For each face:
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Unique Tracking ID (when processing a video file, the same ID on each frame belongs to the same person)
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The most similar reference face ID
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Degree of similarity to the reference face
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Up to 5 facial landmark points
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The system is able to to write the processed video to a video file.
This project is used by the following:
- Kaduna State University
- Daton
- Schematic block diagram of a Facial Recognition System
- Use case diagram illustrating the system behaviour
- Flow chart of the system
- Dlib, Numpy, OpenCV, Flask
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Clone the repo $ git clone https://github.com/Davisonyeas/facial_recognition.git
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Change your directory to the cloned repo and create a Python virtual environment named 'face_recog' $ mkvirtualenv face_recog
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Now, run the following command in your Terminal/Command Prompt to install the libraries required $ pip3 install -r requirements.txt
python app.py
You have completed a Computer Vision project that can now be deployed.
Feel free to file a new issue with a respective title and description on the this face recognition repository. If you already found a solution to your problem, I would love to review your pull request!
Made by Davis Onyeoguzoro
Feel free to mail me for any doubts/query ✉️ [email protected]
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