Hybrid image summarization

Hao Xu, Jingdong Wang, Xian-Sheng Hua, Shipeng Li

Abstract: In this paper, we address a problem of managing tagged images with hybrid summarization. We formulate this problem as finding a few image exemplars to represent the image set semantically and visually and solve it in a hybrid way by exploiting both visual and textual information associated with images. We propose a novel approach, called Homogeneous and Heterogeneous Message Propagation (H2MP), which extends affinity propagation that only works over homogeneous relations to heterogeneous relations. The summary obtained by our approach is both visually and semantically satisfactory. The experimental results demonstrate the effectiveness and efficiency of the proposed approach.