Weakly-supervised construction of a repository of iconic images

We present a first attempt at semi-automatically harvesting a dataset of iconic images.
Iconic images are depicting objects or scenes, which arouse associations to abstract
topics. Our method starts with representative topic-evoking images from Wikipedia, which
are labeled with relevant concepts and entities found in their associated captions. These
are used to query an online image repository (i.e., Flickr), in order to further acquire
additional examples of topic-specific iconic relations. To this end, we leverage a
combination of visual similarity measures, image clustering and matching algorithms to
acquire clusters of iconic images that are topically connected to the original seed
images, while also allowing for various degrees of diversity. Our first results are
promising in that they indicate the feasibility of the task and that we are able to build
a first version of our resource with minimal supervision.