Interactive tool for image annotation using a semi-supervised and hierarchical approach

This paper presents a semi-automatic tool, called IGAnn (Interactive image ANNotation), that assists users in annotating textual labels with images. IGAnn performs an interactive retrieval-like procedure: the system presents the user with images that have higher confidences, and then the user determines which images are actually relevant or irrelevant for a specified label. By collecting relevant and irrelevant images of iterations, a hierarchical classifier associated with the specified label is built using our proposed semi-supervised approach to compute confidence values of unlabeled images. This paper describes the system interface of IGAnn and also demonstrates quantitative experiments of our proposed approach.

► An easy-to-use tool is designed for interactive image annotation, called IGAnn.
► IGAnn can assist users in annotating textual labels with images.
► We design a retrieval-like procedure to interactively annotate labels with images.
► Hierarchical classifiers are constructed using a semi-supervised approach in IGAnn.