Abstract
Automatically generated route instructions are common in modern cars, but for indoor environments, such systems hardly exist, possibly due to the fundamental difference of street networks and indoor environments. Indoor environments often lack the clear decision points present in street networks and involve a spatially complex layout. Therefore, good route instructions for indoor environments should provide context by relating instructions to environmental features—they need to describe and locate objects. This paper is concerned with automatic generation of in-advance route instructions for indoor scenarios. Motivated by empirical research, we propose a probabilistic framework for generating referring expressions using vague properties and graded models of spatial relations. We discuss the relevance of this framework for generating indoor route instructions and demonstrate the appropriateness of this approach in case studies.
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Mast, V., Wolter, D. (2013). A Probabilistic Framework for Object Descriptions in Indoor Route Instructions. In: Tenbrink, T., Stell, J., Galton, A., Wood, Z. (eds) Spatial Information Theory. COSIT 2013. Lecture Notes in Computer Science, vol 8116. Springer, Cham. https://doi.org/10.1007/978-3-319-01790-7_11
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DOI: https://doi.org/10.1007/978-3-319-01790-7_11
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