Analyzing perspective line drawings using hypothesis based reasoning

One of the important issues in the middle levels of computer vision is how world knowledge should be gradually inserted into the reasoning process. In this dissertation, we develop a technique which uses hypothesis based reasoning to reason about perspective line drawings using only the constraints supplied by the equations of perspective geometry. We show that the problem is NP complete, and that it can be solved using modular inference engines for propagating constraints over the set of world level entities. We also show that theorem proving techniques, with their attendant complexity, are not necessary because the real valued attributes of the world can be computed in closed form based only on the spatial relationships between world entities and measurements from the given image.