Multi-level Log-Based Relevance Feedback Scheme for Image Retrieval

摘要：

Relevance feedback has been shown as a powerful tool to improve the retrieval performance of content-based image retrieval (CBIR). However, the feedback iteration process is tedious and timeconsuming. History log consists of valuable information about previous users perception of the content of image and such information can be used to accelerate the feedback iteration process and enhance the retrieval performance. In this paper, a novel algorithm to collect and compute the log-based relevance of the images is proposed. We utilize the multi-level structure of log-based relevance and fully mine previous users perception of content of images in log. Experimental results show that our algorithm is effective and outperforms previous schemes.

关键词： multi-level log-based relevance content-based image retrieval

作者: Huanchen Zhang Weifeng Sun Shichao Dong Long Chen Chuang Lin

作者单位: School of Software of Dalian University of Technology,116620 Dalian Liaoning, China

会议类型: 国际会议

会议名称: 6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)

会议地点: 重庆

会议语种:英文

页码: 545-552

在线出版日期: 2010-11-19（万方平台首次上网日期，不代表论文的发表时间）