Improving Saliency Detection Based on Modeling Photographer's Intention
Xiaoying Ding, Zhenzhong Chen · IEEE Transactions on Multimedia · 2018
A photographer's intention towards a photo evokes the viewer's attentional response. By analyzing the photographer's intention, we can have a better understanding of what the photographers want to convey to the viewers, thus helping to improve image analyzing and understanding. In this paper, a novel method is presented to improve saliency detection based on exploring the relationship between the photographer's intention and the viewer's attention. An intention rate is derived to quantify the intention and integrated with traditional saliency detection in a unified framework accordingly. We evaluate the proposed scheme with several classic saliency detection algorithms on different datasets. The experimental results demonstrate the superior improvements of our method.