Interactive Demo

Computer Vision
Live Demo

This is the same gesture recognition tech from my MEng project. Real-time hand tracking and gesture classification, running entirely in your browser via MediaPipe. No data leaves your device.

Live · In-Browser MediaPipe Hands 21 Hand Landmarks 60fps Target Zero Data Collection
FPS: --

Gesture Recognition

Show your hand to the camera. The model will detect and classify your gesture in real-time using 21 landmark points.

01

Webcam Capture

Video frames are captured from your webcam at 30-60fps and processed entirely on-device using WebGL acceleration.

02

21 Landmark Detection

MediaPipe Hands detects 21 3D hand keypoints — fingertips, joints, wrist — with sub-millimetre relative accuracy.

03

Geometric Classification

Joint angles and relative positions are computed. Gesture rules classify the hand state — the same approach used in my MEng smart glasses project.

04

Real-Time Output

Results render at 60fps with skeleton overlay. In production systems, these outputs trigger robot control, HMI events, or automation commands.

Demo Running Client-Side · No Data Collected