Connecting people in photo-sharing sites by photo content and user annotations

Popular photo-sharing sites have attracted millions of people and helped construct massive social networks in Cyberspace. Different from traditional social relationships, users actively interact in groups where common interests are shared on certain types of events or topics captured by photos and videos. Contributing images to an interest group would greatly promote interactions between users and expand their social networks. In this work, we intend to produce automatic recommendations of a user's images to suitable photo-sharing groups. To this end, we begin with analyzing user annotations and modeling the shared images in a group. Both visual content and annotation context are then integrated to understand the events or topics depicted in those images. Experiments on over 14000 user images demonstrate the feasibility of the proposed approach.