Describing Spatial Relationships between Objects in Images in English and French

Abstract

The context for the work we report here is the automatic description of spatial relationships between pairs of objects in images. We investigate the task of selecting prepositions for such spatial relationships. We describe the two datasets of object pairs and prepositions we have created for English and French, and report results for predicting prepositions for object pairs in both of these languages, using two methods: (a) an existing approach which manually fixes the mapping from geometrical features to prepositions, and (b) a Naive Bayes classifier trained on the English and French datasets. For the latter we use features based on object class labels and geometrical measurements of object bounding boxes. We evaluate the automatically generated prepositions on unseen data in terms of accuracy against the human-selected prepositions.