The problem of automatically learning knowledge-directed control strategies is considered. In particular, the authors address the problem of learning object-specific recognition strategies from object descriptions and sets of interpreted training images. A separate recognition strategy is developed for every object in the domain. The goal of each recognition strategy is to identify any and all instances of the object in an image, and give the 3-D position (relative to the camera) of each instance. The goal of the learning process is to build a strategy that minimizes the expected cost of recognition, subject to accuracy constraints imposed by the user.<>


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    Title :

    Learning 3D object recognition strategies


    Contributors:


    Publication date :

    1990-01-01


    Size :

    459425 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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