KDEVIR at ImageCLEF 2015 Scalable Image Annotation, Localization, and Sentence Generation task: Ontology based Multi-label Image Annotation

In this paper, we describe our participation in the ImageCLEF 2015 Scalable Concept Image Annotation task. In this participation, we propose an approach of image annotation by using ontology at several steps of supervised learning with noisy unlabeled data. In this regard, we construct tree-like ontology for each annotating concept of images using WordNet and Wikipedia. The constructed ontologies are exploited throughout the proposed framework including several phases of training and testing of one-vs-all SVM classifiers. Several classifiers are trained on local or global visual features separately and results are ensemble using the classifiers’ probability scores. The result turns out that our system achieves an average performance in this task.