Diversity in Image Retrieval: DCU at ImageCLEFPhoto 2008

DCU participated in the ImageCLEF 2008 photo retrieval task, which aimed to evaluate diversity in Image Retrieval, submitting runs for both the English and Random language annotation conditions. Our approaches used text-based and image-based retrieval to give baseline runs, with the the highest-ranked images from these baseline runs clustered using K-Means clustering of the text annotations, with representative images from each cluster ranked for the final submission. For random language annotations, we compared results from translated runs with untranslated runs. Our results show that combining image and text outperforms text alone and image alone, both for general retrieval performance and for diversity. Our baseline image and text runs give our best overall balance between retrieval and diversity; indeed, our baseline text and image run was the 2nd best automatic run for ImageCLEF 2008 Photographic Retrieval task. We found that clustering consistently gives a large improvement in d...

• Type: Conference
• Year: 2008
• Where: CLEF
• Authors: Neil O'Hare, Peter Wilkins, Cathal Gurrin, Eamonn Newman, Gareth J. F. Jones, Alan F. Smeaton
• Keywords: Baseline Runs, CLEF 2008, Image, Information Technology, Random Language Annotations