Active learning methods have been considered with an increasing interest in the content-based image retrieval (CBIR) community. In this article, we propose an efficient method based on active learning strategy to retrieve large image categories. At each feedback step, the system optimizes the image set presented to the user in order to speed up the retrieval. Experimental tests on COREL photo database have been carried out.
['Philippe Henri Gosselin', 'Matthieu Cord']
RETIN AL: an active learning strategy for image category retrieval