关键词: 协同滤波, 混合概率模型, 图像自动标注, 增量关联规则, 日志

Abstract: The potential image semantic information in feedback logs helps to improve the quality of image automatic annotation, but the noisy and one-sidedness of the log restrict its function. So it proposes a log-based collaborative automatic image annotation algorithm. It uses incremental association rule to mine log messages according to its characteristics to remove the noisy data and expand the amount of image annotation words with the thought of collaborative filtering. Combining the relationship of the annotation words from the WordNet and the low-level image features, it can accomplish image automatic annotation with adoption of hybrid probabilistic model. The experimental results based on Corel5K and Internet image set show that the proposed algorithm can reduce the negative effects from noisy and one-sidedness of the log data, and improve the performance and efficiency of the automatic image annotation.

Key words: collaborative filtering, hybrid probabilistic model, image automatic annotation, incremental association rules, log