Abstract
In this contribution knowledge-based image understanding is treated. The knowledge is coded declaratively in a production system. Applying this knowledge to a large set of primitives may lead to high computational efforts. A particular accumulating parsing scheme trades soundness for feasibility. Per default this utilizes a bottom-up control based on the quality assessment of the object instances. The point of this work is in the description of top-down control rationales to accelerate the search dramatically. Top-down strategies are distinguished in two types: (i) Global control and (ii) localized focus of attention and inhibition methods. These are discussed and empirically compared using a particular landmark recognition system and representative aerial image data from GOOGLE-earth.
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Michaelsen, E., Arens, M., Doktorski, L. (2009). Interaction of Control and Knowledge in a Structural Recognition System. In: Mertsching, B., Hund, M., Aziz, Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science(), vol 5803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04617-9_10
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DOI: https://doi.org/10.1007/978-3-642-04617-9_10
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