Robust Image Annotation Refinement via Graph-Based Learning

摘要：

Image annotation has been an active research topic in recent years. However, the state of art image annotation methods are often unsatisfactory, in this paper, we presented a novel image annotation refinement to improve the performance of automatic image annotation. Firstly, the initial pair-wise similarities of words is computed based on the co-occurrence of training sets, Then the topic relation is mined by generating the topic bag. Finally, the candidate annotations are re-ranked by embedding the refined word relation. The experiments over Corel images have shown that embedding topic relation is beneficial in image annotation.

关键词： image annotaion graph-based learning label propagation

作者: Xiaohong Hu Xu Qian Lei Xi Xinming Ma

作者单位: School of Information and Management Science, Henan Agricultural University, Zhengzhou,450002, China School of Mechanical Electronic and Information Engineering, China University of Mining and Technolo School of Information and Management Science, Henan Agricultural University, Zhengzhou,450002, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3934-3937

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）