Interactive Material Annotation on 3D Scanned Models leveraging Color-Material Correlation

3D scanning has made it possible to generate 3D models from real objects. Although 3D scanning can capture an object’s shape and color texture, it is still technically difficult to analyze and reproduce material properties such as metalness, roughness, and transparency. Therefore, they need to be explicitly annotated after the scanning process. However, existing methods are highly labor-intensive such as a simple brush painting that requires delicate and inefficient handwork. To make this process more efficient and accurate, we propose a system that mitigates the costs by introducing a texture-aware annotation pipeline. This method is based on the observation that material distribution is correlated to color distribution. We segment the 3D surface into areas based on color similarity and let users annotate materials using the segmentations as masks. In an empirical user study, the participants could make quality annotations in a short time.