Scene and viewpoint based visual summarization for landmarks
Visual summarization of landmarks is an important task for applications, such as landmark organization, search and browsing. In this work, we make the first attempt towards landmark summarization by simultaneously considering both the scenes (e.g., sunny view and night view) and viewpoints (e.g., front-side and close-distant viewpoint). In the proposed framework of landmark summarization, we first group images into different clusters by viewpoints, then the distinctive scenes for each viewpoint cluster are discovered by the proposed scene-viewpoint based theme modeling. Compared with the existing topic models, our model is capable of mining scene-viewpoint themes directly from all viewpoint clusters and meanwhile differentiating among these themes by viewpoints. The landmark summary is generated by the discovered scene-viewpoint themes, where each theme is represented by the selected images with one certain scene and viewpoint. The experimental results validate the proposed method and demonstrate its advantage in improving user experience.