Single View Reconstruction Using Shape Grammars for Urban Environments

In this paper we introduce a novel approach to single view reconstruction using shape grammars. Our approach consists in modeling architectural styles using a set of basic shapes and a set of parametric rules, corresponding to increasing levels of detail. This approach is able to model elaborate and varying architectural styles, using a tree representation of variable depth and complexity. Towards reconstruction, the parameters of the rules are optimized using image-based and architectural costs. This is done through an efficient MRF formulation based on the shape grammar itself. The resulting framework can produce precise 3D models from single views, can deal with lack of texture and the presence of occlusions and specular reflections, while maintaining the ability to cope with very complex architectural styles. Promising results demonstrate the potential of our approach.