Overview

This project, developed as part of my university work, explores the integration of computer vision into Vectorworks, a leading CAD and BIM software. The goal was to investigate how gesture-based input, powered by Python and OpenCV, could influence architectural design, particularly in fields like kinetic architecture, interactive façades, and urban installations.

By leveraging hand and face detection along with finger movement tracking, this project demonstrates how real-time user gestures can dynamically affect architectural designs. These interactions could pave the way for more responsive building components and creative urban spaces that adapt to human movement.

Technologies

• Vectorworks (Marionette Tool) for parametric design integration.
• Python for scripting automation.
• OpenCV for real-time hand and face detection.

Key Features

Hand and Face Detection with Distance-based Interaction

The first feature uses OpenCV to detect hand and face positions and calculate their distance from the camera. This data is extracted and applied to a grid of squares within Vectorworks, where the size of each square adjusts dynamically based on proximity. This opens possibilities for responsive design elements in architecture, such as kinetic façades and interactive installations.