CLEF2008 Image Annotation Task: an SVM Confidence-Based Approach

This paper presents the algorithms and results of the “idiap” team participation to the ImageCLEFmed annotation task in 2008. On the basis of our previous experience in 2007 we decided to integrate two different local structural and textural descriptors. Cues are combined through concatenation of feature vectors and through the MultiCue Kernel. The challenge this year asked to annotate images coming mainly from classes with only few training examples. We tackled the problem on two fronts: (1) we introduced a further integration strategy using SVM as an opinion maker; (2) we enriched the poorly populated classes adding virtual examples. We submitted several runs considering different combination of the proposed techniques. The run using jointly the feature concatenation, the confidence-based opinion fusion and the virtual examples, scored 74.92 ranking first among all submissions.