Visualizing multimodal image collections

This paper presents two different strategies for visualizing multimodal image collections, which are based on a representation strategy that fuses text and visual content in the same latent space. This latent space allows to find semantic groups of images, which are used to select image prototypes to build a semantic visualization. The first strategy is a graph-based visualization in which edges represent image similarities and vertices represent images. The second is a multimodal visualization in which a set of image prototypes surround a semantic tag cloud. Thus, we built a system prototype in order to evaluate the strategies. Results show that the propose strategy is promising and it could be used in a real image exploration system to improve the image collection exploration process.