Generation and application of rules for quality dependent faade reconstruction
Frequently, terrestrial LiDAR and image data are used to extract high resolution building geometry like windows, doors and protrusions for three-dimensional (3D) faade reconstruction. However, such a purely data driven bottom-up modelling of faade structures is only feasible if the available observations meet considerable requirements on data quality. Errors in measurement, varying point densities, reduced accuracies, as well as incomplete coverage affect the achievable correctness and reliability of the reconstruction result. While dependence on data quality is a general disadvantage with data driven bottom-up approaches, model based top-down reconstructions are much more robust. Algorithms introduce knowledge about the appearance and arrangement of objects. Thus, they cope with data uncertainty and allow for a procedural modelling of building structures in a predefined architectural style, which is inherent in grammar or model descriptions. We aim at a quality sensitive faade reconstruction which is on the one hand robust against erroneous and incomplete data, but on the other hand not subject to prespecified rules or models. For this purpose, we combine bottom-up and top-down strategies by integrating automatically inferred rules into a data driven reconstruction process. Faade models reconstructed during a bottom-up method serve as a knowledge base for further processing. Dominant or repetitive features and regularities as well as their hierarchical relationship are detected from the modelled faade elements and automatically translated into rules. These rules together with the 3D representations of the modelled faade elements constitute a formal grammar. It holds all the information which is necessary to reconstruct faades in the style of the given building. The paper demonstrates that the proposed algorithm is very flexible towards different data quality and incomplete sensor data. The inferred grammar is used for the verification of the faade model produced during the data driven reconstruction process and the generation of synthetic faades for which only partial or no sensor data is available. Moreover, knowledge propagation is not restricted to faades of one single building. Based on a small set of formal grammars derived from just a few observed buildings, faade reconstruction is also possible for whole districts featuring uniform architectural styles.
building three-dimensional modelling architecture interpretation