Dynamic Queries with Relevance Feedback for Content Based Image Retrieval

A novel relevance feedback scheme utilizing dynamic queries for content based image retrieval systems is proposed, where the retrieval results are updated instantly based on the user's feedback. The user is expected to label at least one image as positive or negative, revealing the gist of the expected retrieval results. Then the retrieval results are updated dynamically, without any further user interaction, based on the similarity of the query and the selected image in different feature spaces increasing the semantic accuracy of the retrieval. The proposed method not only invalidates the drawbacks of current relevance feedback systems in terms of user experience, but also provides an innovative stand point for the relevance feedback scheme as well.