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Cognitive Processing
Erschienen in: Cognitive Processing 1/2011

01.02.2011 | Research Report

Interpreting spatial language in image captions

verfasst von: Mark M. Hall, Philip D. Smart, Christopher B. Jones

Erschienen in: Cognitive Processing | Ausgabe 1/2011

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Abstract

The map as a tool for accessing data has become very popular in recent years, but a lot of data do not have the necessary spatial meta-data to allow for that. Some data such as photographs however have spatial information in their captions and if this could be extracted, then they could be made available via map-based interfaces. Towards this goal, we introduce a model and spatio-linguistic reasoner for interpreting the spatial information in image captions that is based upon quantitative data about spatial language use acquired directly from people. Spatial language is inherently vague, and both the model and reasoner have been designed to incorporate this vagueness at the quantitative level and not only qualitatively.
Vorheriger Artikel Multimodal cognitive interface for robot navigation
Nächster Artikel The effect of occlusion on the semantics of projective spatial terms: a case study in grounding language in perception

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Fußnoten
4
A toponym is a place with a recognisable name used in communication, where a “place” is often defined simply as a meaningful geographic location (Goodchild and Hill 2008).
 
5
There is also the possibility of using an approach based on supervaluation (see Bennet 2001 or Kulik 2001, which allows for the creation of a set of boundaries that describe the gradual transition from the definite to the definitely not area, similar to iso-lines used to represent height on conventional maps. The fuzzy methodology seems to be more frequently used and thus is given prominence.
 
7
To avoid a bias being introduced by a small group of frequent contributors producing most of the captions, only one caption per contributor was considered. This reduces the number of captions from around 350,000 to 580.
 
8
See “Appendix” for the technical aspects of the vague field.
 
9
See “Appendix” for details on how it is calculated.
 
10
As Lodge (1984) phrases it “It’s not so easy, every decoding is a new encoding”.
 
11
This can be seen in the evaluation results in “Evaluation experiment” where the low inter-participant agreement indicates the large number of different possible encodings and decodings.
 
12
Named Entity Recognition is the task of identifying noun phrases that refer to specific individuals whether these be people, companies, dates, ....
 
14
An example of how this additional information might help is in the caption “Flowers near Stackpole Head”, where Stackpole Head is a coastal headland, and the inclusion of the knowledge that the photograph is of “Flowers” could restrict the probable area where the photograph was taken to the land-side, whereas if the subject were “Sailing boat” then the sea-facing “near” area would be more likely. This kind of knowledge processing was decided to be beyond scope of this paper and thus the information is discarded.
 
15
The results for “east of” will not be reported as they are analogous to the “north of” results and the “between” results due to space constraints.
 
16
0 and 1—high agreement, 2—medium agreement, or 3—higher–low agreement.
 
17
For north and south this is the vertical axis, for east and west the horizontal axis.
 
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Metadaten
Titel
Interpreting spatial language in image captions
verfasst von
Mark M. Hall
Philip D. Smart
Christopher B. Jones
Publikationsdatum
01.02.2011
Verlag
Springer-Verlag
Erschienen in
Cognitive Processing / Ausgabe 1/2011
Print ISSN: 1612-4782
Elektronische ISSN: 1612-4790
DOI
https://doi.org/10.1007/s10339-010-0385-5

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