Map-Driven Image Interpretation by Associative Model Indexing
نویسندگان
چکیده
The problem of integrating territorial information within a multisensor vision system for autonomous-vehicle control is addressed. Environmental information is used to improve recognition results and to locate a vehicle's position in the coordinate reference frame of a map. To this end, a hypothesis-and-test search mechanism has been developed, which is based on an associative phase and a symbolic. In particular, an associative memory is first used to address the possible territorial area where the scene under examination may have been acquired. This guess is then verified by a symbolic recognition system using a model-driven strategy.
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