@article{oai:sucra.repo.nii.ac.jp:00013808,
 author = {CAO, Lu and LAM, Antony and 小林, 貴訓 and 久野, 義徳 and 加地, 大介},
 issue = {2},
 journal = {IIEEJ Transactions on Image Electronics and Visual Computing},
 month = {},
 note = {Spatial descriptions are one of the most effective methods to enable interlocutors to identify which object is being discussed in discourse. In this paper, we propose a framework that can identify an object whose positional relation with another object is indicated verbally by a human. To this end, we construct a spatial knowledge ontology. The ontology is enriched by Description Logic (DL) of concepts, which allows discovering hidden knowledge. We also propose a Spatial Object Dataset that is specifically tailored for our experiments with ontological structures. The dataset currently contains 130 objects and in total of 720 images for object recognition and 360 scenes for spatial recognition. Preliminary experimental results confirmed that the system was able to correctly recognizes human descriptions and identify unknown objects and that understanding human spatial descriptions is efficient for human-machine interaction., text, application/pdf},
 pages = {150--163},
 title = {Understanding Spatial Knowledge : An Ontology-Based Representation for Object Identification},
 volume = {3},
 year = {2015},
 yomi = {コバヤシ, ヨシノリ and クノ, ヨシノリ and カチ, ダイスケ}
}