Efficient 3D-modeling of buildings using a priori geometric object information

The subject of this paper is the research that aims at efficiency improvement of acquisition of 3D building models from digital images for Computer Aided Architectural Design (CAAD). The results do not only apply to CAAD, but to all applications where polyhedral objects are involved. The research is concentrated on the integration of a priori geometric object information in the modeling process. Parallelism and perpendicularity are examples of the a priori information to be used. This information leads to geometric constraints in the mathematical model. This model can be formulated using condition equations with observations only. The advantage is that the adjustment does not include object parameters and the geometric constraints can be incorporated in the model sequentially. As with the use of observation equations statistical testing can be applied to verify the constraints. For the initial values of orientation parameters of the images we use a direct solution based on a priori object information as well. For this method only two sets of (coplanar) parallel lines in object space are required. The paper concentrates on the mathematical model with image lines as the main type of observations. Advantages as well as disadvantages of a mathematical model with only condition equations are discussed. The parametrization of the object model plays a major role in this discussion.