Clustering for Photo Retrieval at Image CLEF 2008

This paper presents the first participation of the University of Ottawa group in the Photo Retrieval task at Image CLEF 2008. Our system uses Lucene for text indexing and LIRE for image indexing. We experiment with several clustering methods in order to retrieve images from diverse clusters. The clustering methods are: k-means clustering, hierarchical clustering, and our own method based on WordNet. We present results for thirteen runs, in order to compare retrieval based on text description, to image-only retrieval, and to merged retrieval, and to compare results for the different clustering methods. Keywords Information retrieval, image retrieval, photographs, text retrieval, kmeans clustering, agglomerative clustering, WordNet-based clustering.

• Type: Conference
• Year: 2008
• Where: CLEF
• Authors: Diana Inkpen, Marc Stogaitis, François DeGuire, Muath Alzghool
• Keywords: CLEF 2008, Clustering Methods, Information Management, K-means Clustering, Photo Retrieval Task