Improving the representation of image descriptions for semantic image retrieval with RDF

• Published in: Journal of visual communication and image representation Vol. 73; p. 102934
• Main Authors: Chen, Hua, Guo, AiBin, Ni, Wenlong, Cheng, Yan
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-11-2020
• Subjects: Cross-lingual retrieval; Image representation; Image retrieval; RDF; Semantic image retrieval; RDF; Image retrieval; Semantic image retrieval; 41A10; 65D05; Image representation; 65D17; 41A05; Cross-lingual retrieval
• ISSN: 1047-3203; 1095-9076
• DOI: 10.1016/j.jvcir.2020.102934

The past few years have witnessed a surge of interest in many topics at the intersection of natural language processing and computer vision. In particular, using objects together with their attributes and relations to represent images or interpret languages has been proved useful across a wide variety of applications. The goal of this work is to provide an improved RDF-based model to represent images for enhancing textual based image retrieval. We use natural language processing tools to obtain a set of objects, attributes and relations; and then model them into graphical structures with RDF-based model. We also conduct some preliminary experiments to show how to handle textual based image retrieval for complex queries or multilingual queries. The experimental results show that our approach improves the representation of image descriptions, which is suitable for enhancing image retrieval with high-level semantics.