FIRE in ImageCLEF 2005: Combining Content-Based Image Retrieval with Textual Information Retrieval [chapter]

Thomas Deselaers, Tobias Weyand, Daniel Keysers, Wolfgang Macherey, Hermann Ney
2006 Lecture Notes in Computer Science  
In this paper we describe the methods we used in the 2005 ImageCLEF content-based image retrieval evaluation. For the medical retrieval task, we combined several low-level image features with textual information retrieval. Combining these two information sources, clear improvements over using one of these sources alone are possible. Additionally we participated in the automatic annotation task, where we used FIRE, our content-based image retrieval system, on the one hand and a subimage based
more » ... hod for object classification on the other hand. The results achieved are very good. In particular, we obtained the first and the third rank in the automatic annotation task out of 44 submissions from 12 groups.
doi:10.1007/11878773_72 fatcat:cgnk3hozt5cvnbo7mg23ditoke