Graph based Learning for Robust Image Annotation with Relation Propagation
Image annotation has been an active research topic in recent years. In this paper, we presented a novel graph-based learning approach for robust image annotation with relation propagation. In order to capture the complex distribution of image data, we propose a similarity refinement approach to improve the robustness of traditional label propagation. Then the refined affinity matrix is applied to label propagation. Thus, the traditional pair-wise similarity is fused with the similar scores of its neighbors. And the proposed image annotation approach can propagate the labels from the labeled images to the whole image database using the fusing neighborhoods. The experiments over Corel images have shown that embedding relation propagation is beneficial in image annotation.
image annotation graph based learning relation propagation
Genyi Niu
School of Information Management,Wuhan University, Wuhan Hubei.China Henan Agriculture University Library,Zhengzhou Henan,China
国际会议
太原
英文
223-226
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）