This study proposes an innovative methodology for documenting and semantically analysing cultural heritage by integrating artificial intelligence (AI) with a photogrammetric 3D model. The case study is the Trajan’s Column in Rome, a monumental structure adorned with a continuous helical relief depicting Emperor Trajan’s Dacian campaigns. AI-driven semantic segmentation is used to identify key elements (such as human figures, battle scenes and natural motifs) within the digitised sculptural narrative. Starting from a high-resolution photogrammetric 3D model, the column’s texture is divided into multiple segments and a multimodal large language model (MLLM) is applied to produce context-aware segmentation masks via natural language prompts. Results are then projected onto the 3D geometry and visualised through a web-based 3D viewer.
