Geometric reasoning for constructing 3D scene descriptions from images
Ellen Walker, Martin Herman · 1989
Abstract There are many applications for a vision system which derives a three-dimensional model of a scene from one or more images and stores the model for easy retrieval and matching. The derivation of a 3D model of a scene involves transformations between four levels of representation: images, 2D features, 3D structures, and 3D geometric models. Geometric reasoning is used to perform these transformations, as well as for the eventual model matching. Since the image formation process is many-to-one, the problem of deriving 3D features from 2D features is ill-constrained. Additional constraints may be derived from knowledge of the domain from which the images were taken. The 3D MOSAIC system has successfully used domain specific knowledge to drive the geometric reasoning necessary to acquire 3D models for complex real-world urban scenes. To generalize this approach, a framework for the representation and use of domain knowledge for geometric reasoning for vision is proposed.