Cross-modality based celebrity face naming for news image collections
For automatically mining the underlying relationships between different famous persons in daily news, for example, building a news person based network with the faces as icons to facilitate face-based person finding, we need a tool to automatically label faces in new images with their real names. This paper studies the problem of linking names with faces from large-scale news images with captions. In our previous work, we proposed a method called Person-based Subset Clustering which is mainly based on face clustering for all face images derived from the same name. The location where a name appears in a caption, as well as the visual structural information within a news image provided informative cues such as who are really in the associated image. By combining the domain knowledge from the captions and the corresponding image we propose a novel cross-modality approach to further improve the performance of linking names with faces. The experiments are performed on the data sets including approximately half a million news images from Yahoo! news, and the results show that the proposed method achieves significant improvement over the clustering-only methods.
cross-modality affinity propagation cluster face classification rank aggregation