Accessible Hand Gesture PC Control

I’m building a computer-side accessibility layer that translates real-time hand movements, captured through an ordinary webcam, into system commands such as click, drag, scroll and shortcut activation. The goal is to give users with limited mobility an intuitive alternative to a mouse or keyboard, so recognition accuracy and low-latency response are essential.

I already know the interface points I want to hit—virtual mouse events, configurable hot-keys and an on-screen overlay for feedback—but I need an experienced developer to design and train the hand-gesture recognition pipeline, wire it into the operating system (Windows first, cross-platform later), and leave me with clear documentation so the tool can be maintained and expanded.

You’re free to pick the tech stack that suits you best; OpenCV, MediaPipe, TensorFlow, PyTorch, or a combination are all fine so long as the final executable runs locally without cloud dependence.

Deliverables
• A compiled desktop application (or installable Python bundle) that recognises at least five distinct hand gestures and maps them to system actions
• A simple GUI for calibrating the camera, adjusting sensitivity and remapping gestures
• Source code with inline comments plus a short setup & usage guide
• A brief demo video that shows each gesture triggering its assigned action in real time

Acceptance criteria: on a mid-range laptop with a 720p webcam the system should detect gestures within 150 ms, achieve at least 95 % accuracy in well-lit conditions, and recover gracefully from occlusion or mis-fires.

If this excites you and you can hit the performance marks, let’s talk timeline and milestones.