This work addresses the problem of the representation of spatial relationships between symbolic objects in images. We have studied the distribution of several categories of relationships in LabelMe, a public database of images where objects are annotated manually and online by users. Our objective is to build a cartography of the spatial relationships that can be encountered in a representative database of images of heterogeneous content, with the main aim of exploiting it in future applications of Content-Based Image Indexing (CBIR), such as object recognition or retrieval. In this paper, we present the framework of the experiments made and give an overview of the main results obtained, as an introduction to the website dedicated to this work, whose ambition is to make available all these statistics to the CBIR community. © 2011 Springer-Verlag.
CITATION STYLE
Hoàng, N. V., Gouet-Brunet, V., & Rukoz, M. (2011). A cartography of spatial relationships in a symbolic image database. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6854 LNCS, pp. 377–385). https://doi.org/10.1007/978-3-642-23672-3_46
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