Using Multiple Information Sources in a Computational Vision System

Abstract

One method of resolving the ambiguity inherent in interpreting images is to add different sources of information. The multiple information source paradigm emphasizes the ability to utilize knowledge gained from one source that may not be present in another. A schema-based system has been developed that can take advantage of multiple sources of information.Schemata are combined into a semantic network via the relations decomposition, specialization,instance of, and neighbour. Control depends on the structure of the evolving network and a cycle of perception. Schemata cooperate by message passing so that attention can be directed where it will be most advantageous. This system has been implemented to interpretaerial photographs of small urban scenes. Geographic features are identified using up to three information sources: the intensity image, a sketch map, and user guidance. The product is a robust system where the accuracy of the results reflects the quality and amount of data provided. Images of several geographic locales have been analyzed, and positive results are reported.