Face Recognition Project

This project uses JavaScript combined with the face-api.js library for real-time face detection and comparison. It enables seamless real-time face detection and identification by leveraging modern machine learning techniques in JavaScript.

Technology Used

• JavaScript: Core language for implementing functionality.
• face-api.js: A machine learning library built on top of TensorFlow.js that provides pre-trained models for face detection, landmark detection, face recognition, and more.

How Face Detection and Comparison Work

1. Face Detection

• Models like tinyFaceDetector, ssdMobilenetv1, and faceLandmark68Net are preloaded using face-api.js.
• The system integrates with a webcam to capture real-time video streams.
• Faces in the video stream are detected using the detectAllFaces method, which identifies faces and marks their landmarks (e.g., eyes, nose, mouth).

2. Face Descriptor Extraction

• Each detected face is processed to generate a descriptor, which is a numerical representation of key facial features.
• Pre-uploaded images of individuals are also processed to generate descriptors, which are then labeled (e.g., a person's name).

3. Face Matching

• Detected face descriptors are compared against the labeled descriptors using the FaceMatcher class from face-api.js.
• A similarity threshold determines if a match is found, and the matched label (e.g., a name) is displayed on the video stream.

4. Image Upload and Labeling

• Users can upload images via a form, where each image is labeled with the uploader's name.
• The server saves these images and updates a JSON file (imageList.json) with metadata such as filenames and labels.

5. Real-time Comparison

• The FaceMatcher continuously compares faces detected in the webcam feed with stored descriptors.
• Matching results are displayed on a canvas overlay, showing bounding boxes around faces and their corresponding labels.

Installation and Setup

Follow these steps to get the project running:

1. Clone the repository:

   git clone https://github.com/Wilfred1097/face-recognition.git
   cd face-recognition

2. Install dependencies: Run the following command to install all required dependencies:

   npm install

3. Start the server: Launch the server with:

   npm start

4. Access the application: Open your browser and visit http://127.0.0.1:3000 to access the real-time face recognition interface.

Additional Notes

• Ensure your webcam is connected and accessible to allow the application to perform real-time face detection.
• Uploaded images should be renamed to include the full name of the individual (e.g., John_Doe.jpg) before uploading.

References

• face-api.js Documentation