CEA LIST's participation to the Concept Annotation Task of ImageCLEF 2012
Amel Znaidia, Aymen Shabou, Adrian Stefan Popescu, Hervé Le Borgne · CLEF (Online Working Notes/Labs/Workshop) · 2012
This paper describes our participation to the ImageCLEF2012 Photo Annotation Task. We focus on how to use the tags associated to the images to improve the annotation performance. We submitted one textual-only and three multimodal runs. Our first textual model (14) is based on the local soft coding of images tags over a dictionary of most frequent tags. A second model of tag is an adaptation of the TF-IDF model to the social space in order to compute the social relatedness of two tags(9). For the fusion we used a trainable combiner, called stacked generalization (12) which uses predictions from base classifiers to learn a new model. Results have shown that combination of textual and vi- sual features can improve the annotation performance significantly. Our best run achieves 41:59 % in terms of MAP, allowing us to rank 3 rd team.