In this paper, we have developed a novel scheme to incorporate topic network and representativeness-based sampling for achieving semantic and visual summarization and visualization of large-scale collections of Flickr images. First, topic network is automatically generated for summarizing and visualizing large-scale collections of Flickr images at a semantic level, so that users can select more suitable keywords for more precise query formulation. Second, the diverse visual similarities between the semantically-similar images are characterized more precisely by using a mixture-of-kernels and a representativeness-based image sampling algorithm is developed to achieve similarity-based summarization and visualization of large amounts of images under the same topic, so that users can find some particular images of interest more effectively. Our experiments on large-scale image collections with diverse semantics have provided very positive results.
['Jianping Fan', 'Yuli Gao', 'Hangzai Luo', 'Daniel A. Keim', 'Zongmin Li']
A novel approach to enable semantic and visual image summarization for exploratory image search