A Layered Abduction Model of Building Recognition
Toni F. Schenk · Birkhäuser Basel eBooks · 1995
This paper addresses the problem of recognizing buildings from large-scale aerial images on a rather conceptual level. After defining the problem and describing the assumptions and constraints, the object recognition problem is decomposed into different layers, beginning with the preprocessed images and progressing through intermediate levels of raw and segmented surfaces towards a geometric and semantic description of buildings. The interaction of the tasks on every layer is cast as a layered abduction model based on the hypothesis that visual perception is layered abduction. A brief motivation of this hypothesis is provided in the third section, together with a basic background of abduction. The remaining part of the paper is concerned with applying the general abduction model to the problem of building recognition. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.