Object classification is a key differentiator of building information modeling (BIM) from three-dimensional (3D) computer-aided design (CAD). Incorrect object classification impedes the full exploitation of BIM models. Models prepared using domain-specific software cannot ensure correct object classification when transferred to other domains, and research on reconstruction of BIM models using spatial survey has not proved a full capability to classify objects. This research proposed an integrated approach to object classification that applied domain experts' knowledge of shape features and pairwise relationships of 3D objects to effectively classify objects using a tailored matching algorithm. Among its contributions: the algorithms implemented for shape and spatial feature identification could process various complex 3D geometry; the method devised for compilation of the knowledge base considered both rigor and confidence of the inference; the algorithm for matching provides mathematical measurement of the object classification results. The integrated approach has been applied to classify 3D bridge objects in two models: a model prepared using incorrect object types and a model manually reconstructed using point cloud data. All these objects were successfully classified.
|Number of pages||13|
|Journal||Computer-Aided Civil and Infrastructure Engineering|
|Early online date||29 Nov 2017|
|Publication status||Published - Feb 2018|