Abstract
Image interpretation is a dynamic research domain involving not only the detection of objects in a scene but also the semantic description considering context information in the whole scene. Image interpretation problem can be formalized as an abductive reasoning problem, i.e. an inference to the best explanation using a background knowledge. In this work, we present a framework using a tableau method for generating and selecting potential explanations of the given image when the background knowledge is encoded using a description that is able to handle spatial relations.
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Yang, Y., Atif, J., Bloch, I. (2015). Abductive Reasoning Using Tableau Methods for High-Level Image Interpretation. In: Hölldobler, S., , Peñaloza, R., Rudolph, S. (eds) KI 2015: Advances in Artificial Intelligence. KI 2015. Lecture Notes in Computer Science(), vol 9324. Springer, Cham. https://doi.org/10.1007/978-3-319-24489-1_34
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DOI: https://doi.org/10.1007/978-3-319-24489-1_34
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