Summarizing Social Image Search Results using Human Affects
Eunjeong Ko, Eun Yi Kim, Yaohui Yu · 2017
In this paper, we propose the selection of representative images based on human affects. For this, the images are first transformed into the affective space using convolutional neural network (CNN). Thereafter, images are clustered on affective space and then the resulting clusters are ranked based on the proposed three properties ? coverage, affective coherence and distinctiveness. Finally, some representative images are selected from top-ranked clusters. The experiments conducted on Flickr images showed the effectiveness of the proposed method.