An image retrieval method based on analysis of feedback sequence log

Abstract

We present an approach for image retrieval using on-line analysis of feedback sequence log. Our approach is based on user's feedback sequence accumulation and on-line collaborative filtering to predict the semantic correlation between query sample and the images in database. We make use of Edit Distance to evaluate the similarity between the feedback sequence of current retrieval and the prefixes of the records in the feedback log. Integrated with the retrieval method based on the generalized Euclidean distance, the retrieval accuracy can be improved apparently. Experiments over 11,000 images demonstrate that our method achieves significant improvement in retrieval performance compared with conventional methods.