Style-centric image summarization from photographic views of a city
Visual summarization addresses the task of selecting images from an image collection, so that the sampled images would contain representative information which sufficiently highlights the collected visual data. In this paper, we solve the problem of style-centric visual summarization using photographic landmark images of a city. Different from existing works which typically retrieve landmark images based on salient visual appearances, our proposed method is able to produce different sets of summarized images, while each set corresponds to a particular image style. This is achieved by performing unsupervised clustering on images within and across landmark categories, which discovers the common photographic styles from the input image collection. Our experiments will confirm that, compared to standard clustering algorithms, our approach is able to achieve satisfactory summarization outputs with style consistency.