3D scene graph representation and application for intelligent indoor spaces
Existing methods for indoor 3D scene representation focus on object-oriented descriptions,with element representa-tions limited to object-level semantic understanding.These methods lack the ability to express complex relational information within indoor scenes.Addressing the demands of intelligent indoor space tasks,there is a critical need for a structured model that can comprehensively and accurately describe the geometry,semantics,and relationships of indoor elements,while also supporting semantic retrieval and analytical reasoning.Based on the fundamental theory of 3D scene graphs,this paper innova-tively proposes a 3D scene graph representation model tailored for intelligent indoor spaces.It systematically introduces the hi-erarchical organization,geometric representation,semantic description,and relational description methods of indoor 3D scene graphs.A conceptual model is established that uniformly describes the geometry,semantics,and relationships of indoor ele-ments.Additionally,this graph model is compatible with existing 3D scene representation methods,ensuring good data com-patibility.Finally,a comprehensive multi-level relational 3D scene graph model is constructed based on the publicly available IFC model.This model's application capabilities,potential,and limitations are systematically explored and analyzed through applications such as complex scene retrieval and topological analysis,in conjunction with large language models.The results demonstrate that the indoor 3D scene graph model possesses complex computation and analysis capabilities,can be directly in-tegrated with large language models,and enables complex scene analysis applications through simple natural language prompts.
indoor modelinggraph modelIFCCityGMLlarge language model
NETL
NSTL
万方数据
