CGA shape, a novel shape grammar for the procedural modeling of CG architecture, produces building shells with high visual quality and geometric detail. It produces extensive architectural models for computer games and movies, at low cost. Context sensitive shape rules allow the user to specify interactions between the entities of the hierarchical shape descriptions. Selected examples demonstrate solutions to previously unsolved modeling problems, especially to consistent mass modeling with volumetric shapes of arbitrary orientation. CGA shape is shown to efficiently generate massive urban models with unprecedented level of detail, with the virtual rebuilding of the archaeological site of Pompeii as a case in point.

This paper presents a new method for the automatic modeling of architecture. Building designs are derived using split grammars, a new type of parametric set grammar based on the concept of shape. The paper also introduces an attribute matching system and a separate control grammar, which offer the ßexibility required to model buildings using a large variety of different styles and design ideas. Through the adaptive nature of the design grammar used, the created building designs can either be generic or adhere closely to a speciÞed goal, depending on the amount of data available.

et al., is the basis of much of the current research in design methodology and CAD. 1 Mitchell gives an elegant description of the model. 2 He claims that design can be described in words that make up a critical language and such word descriptions can be formalized using the notation of first-order predicate calculus. Design worlds, he says, consist of graphic tokens which, like words, can be manipulated according to certain grammatical rules. 1 See George Stiny, Introduction to Shape and Shape Grammars, Environment and Planning B, 7 (1980): 342-351; William J. Mitchell, The Logic of Architecture: Design, Computation, and Cognition, Cambridge, Massachusetts, MIT Press, 1990; H. Yoshikawa, General Design Theory and a CAD System, in T. Sata and E. Warman (eds), Man-Machine Communications in CAD/CAM, Amsterdam, North-Holland, 1981; R.D. Coyne, M.A. Rosenman, A.D. Radford, M. B

By marrying traditional methods for computer programming with an artistic temperament, we give birth to a new phenomenon: the aesthetic program. Our work builds on visual approaches in programming as well as modeling for software, where I envision a gradual evolution from program to model. The need for the aesthetic model is strengthened with the importance of personalized, individually-tailored, models. I, and my students, have formulated the rube Project methodology around the use of 3D web-based virtual world construction of models. Initial results suggest that these models are artistic, while containing sufficient symbolism and concise metaphoric mapping as to be executable on a computer.

Département d’Histoire de l’art et d’études cinématographiques, Université de Montréal, (Québec) Canada

Frequently, algorithms for 3D facade reconstruction extract high resolution building geometry like windows, doors and protrusions from terrestrial LiDAR and image data. However, such a bottom-up modelling of facade structures is only feasible if the observed data meets considerable requirements on the amount of detail and coverage. For this reason, within our work, the explicit reconstruction of facades is enhanced by the integration of rules. The rules are derived automatically from already reconstructed facades, which serve as knowledge base for further processing. As an example, dominant or repetitive features and regularities as well as their hierarchical relationship are detected from the modelled facade elements. The rules together with the 3D representations of the modelled facade elements constitute a formal grammar. It holds all the information which is necessary to reconstruct facades in the style of the given building. In our approach, they are used for both the verification of the facade model generated during the data driven reconstruction process and the generation of synthetic facades for which no observed sensor data is available. 1.

Abstract not found

Abstract — This paper introduces a work in progress on a new research topic for artificial intelligence. It presents the first stages of research that investigates the capacities of AI to understand the architectural rules that define historic architecture: specifically those of Gothic cathedrals. Gothic architecture has its own logic. It follows rules that are defined by physical and structural constraints as well as by the style of the architecture. This project will analyze specialized descriptions of Gothic architecture and translate them into computer code. On the long run this will result in an intelligent computational model, a program that can understand the structure of a Gothic cathedral and reason about its architecture. This paper introduces the background of this project, sketches a small knowledge base illustrating the approach, and describes the potential impact of this type of research on the study of historic architecture.

We present a novel method for retrieval and classification of 3D building models that is tailored to the specific requirements of architects. In contrast to common approaches our algorithm relies on the interior spatial arrangement of rooms instead of exterior geometric shape. We first represent the internal topological building structure by a Room Connectivity Graph (RCG). Each room is characterized by a node. Connections between rooms like e.g. doors are represented by edges. Nodes and edges are additionally assigned attributes reflecting room and edge properties like e.g area or window size. To enable fast and efficient retrieval and classification with RCGs, we transform the structured graph representation into a vector-based one. We first decompose the RCG into a set of subgraphs. For each subgraph, we compute the similarity to a set of codebook graphs. Aggregating all similarity values finally provides us with a single vector for each RCG which enables fast retrieval and classification. For evaluation, we introduce a classification scheme that was carefully developed following common guidelines in architecture.We finally provide comprehensive experiments showing that the introduced subgraph embeddings yield superior performance compared to state-of-the-art graph retrieval approaches.

This paper presents a work in progress on a new research topic for artificial intelligence. It presents the first stages in a research that investigates the capacities of AI to understand the architectural rules that define historic architecture, more precisely Gothic cathedrals. Gothic architecture has its own logic. It follows