Live Camera Tracking

Real-time face detection and landmark tracking using your webcam

Click "Start Camera" to begin live face tracking
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Interactive Demo

A p5.js simulation of face detection with landmarks, bounding boxes, and mask overlays

Confidence 98.7%
Landmarks 68
FPS 60
Faces 1

Live Recording

Actual face tracking with real-time mask overlay on webcam input

Face Tracking & Masks — real-time face detection and mask overlay demo recording by Afreen Bhumgara

Recording of the face tracking system detecting facial landmarks and applying a dynamic mask in real-time

About This Project

Computer vision meets creative expression

This project explores real-time face tracking and mask overlays using computer vision and machine learning. It detects 68 facial landmarks in live video and applies dynamic masks that follow the user's face movements, expressions, and head rotations in real-time. The system uses a multi-stage pipeline: first a convolutional neural network localizes the face within the frame, then a regression model precisely maps landmark positions for eyes, eyebrows, nose, mouth, and jawline. The mask overlay system uses these landmarks as anchor points, interpolating between them to create smooth, natural-looking augmented reality effects.

Face Detection

Real-time face localization using a CNN-based detector with high accuracy bounding box regression.

Landmark Detection

68-point facial landmark detection mapping eyes, nose, mouth, jawline, and eyebrow positions.

Mask Overlays

Dynamic mask rendering anchored to facial landmarks with real-time expression tracking.

Motion Tracking

Smooth head pose estimation and movement tracking for natural mask alignment.

Technologies

Tools and techniques used in this project

Machine Learning Computer Vision Face Detection Facial Landmarks Mask Overlays Motion Tracking Real-Time Processing p5.js JavaScript Neural Networks CNN AI