We describe building a large-scale image ontology using the WordNet lexical resources. This ontology is based on English words identifying portrayable objects. We reviewed the upper structure and interconnections of WordNet and selected only the branches leading to portrayable objects. This article explains our pruning approach to WordNet. The words, which represent portrayable objects, are then used as queries in our VIKA (VIsual KAtaloguer) system which acquires images through a web image search engine, performs content-based image indexing and clustering. Coherent images form clusters and others are rejected. So images inside clusters mostly represent the object determined by the query, and in this way image collections representing objects are created. An ontology of portrayable objects with representative images in its nodes will be a useful tool for solving the object recognition task.
|Title of host publication||Proceedings of the MUSCLE/ImageCLEF Workshop on Image and Video Retrieval Evaluation, 20 September 2005, Vienna, Austria|
|Place of Publication||Vienna|
|Publisher||Vienna University of Technology|
|Publication status||Published - 2005|