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Semi-Supervised object recognition using flickr images

In this work we present an algorithm for extracting region level annotations from flickr images using a small set of manually labelled regions to guide the selection process. More specifically, we construct a set of flickr images that focuses on a certain concept and apply a novel graph based clustering algorithm on their regions. Then, we select the cluster or clusters that correspond to the examined concept guided by the manually labelled data. Experimental results show that although the obtained regions are of lower quality compared to the manually labelled regions, the gain in effort compensates for the loss in performance.