I Built a Webcam Sign-Language Reader in the Browser (No Cloud)

Short summary

This tutorial demonstrates building a webcam sign-language reader using Google's MediaPipe hand-tracking model running entirely in-browser via WebAssembly. The approach uses geometry-based recognition of 21 hand landmarks to identify raised fingers and simple gestures like counts 0-5, with debounce logic to prevent noise. The author's key insight: most AI products are 20% model and 80% useful engineering on top.

• •MediaPipe hand-tracking runs entirely on-device in the browser via WebAssembly, no cloud upload required
• •21 hand-landmark points analyzed geometrically to recognize finger positions and gestures without trained models
• •Debounce mechanism stabilizes detections over ~12 frames to create clean, usable sign sequences

Generated with AI, which can make mistakes.