Approaches of using a word-image ontology and an annotated image corpus as intermedia for cross-language image retrieval

Abstract

Two kinds of intermedia are explored in ImageCLEFphoto2006. The approach of using a word-image ontology maps images to fundamental concepts in an ontology and measure the similarity between two images by using the kind-of relationship of the ontology. The approach of using an annotated image corpus maps images to texts describing concepts in the images, and the similarity of two images is measured by text counterparts using BM25. The official runs show that visual query and intermedia are useful. Comparing the runs using textual query only with the runs merging textual query and visual query, the latter improved 71%∼119% of the performance of the former. Even in the situation which example images were removed from the image collection beforehand, the performance was still improved about 21%∼43%. © Springer-Verlag Berlin Heidelberg 2007.