Projection-based structural element extraction from point clouds

Extracting structural elements from building-scale point clouds is essential for structural assessment, yet remains difficult in industrial environments due to clutter, occlusions, varying density, and missing faces. We propose a fast extraction pipeline that identifies axis-aligned structural elements through orthogonal projections and 2D histograms, and groups peaks into structural candidates via graph-based clustering. The key parameters operate on an explicit histogram representation, making threshold selection visually interpretable for rapid expert iteration. Our method enables rapid conversion of cluttered scans into simulation-oriented structural primitives suitable for downstream structural analysis workflows.