Real-time Superquadric Representation of Cuboids and Cylinders using Instant Surface Normal Map for Dynamic Object Integration in AR

Abstract

We present a real-time AR system that enables interaction with physical cuboid- and cylinder-shaped objects by representing them as compact superquadrics. Our approach uses Instant Surface Normal (ISN) maps-color images encoding per-pixel geometry-to detect and segment objects based on shape rather than appearance. Superquadric parameters are extracted sequentially, allowing efficient and updatable 3D modeling in real time. Experimental results show accurate detection, consistent segmentation, and reconstruction quality comparable to existing methods, while achieving over 5× faster inference. This system allows physical objects to be seamlessly integrated as interactive elements in dynamic AR environments.