Filter Image Browsing exploiting interaction in image retrieval

In current image retrieval systems the user refines his query by selecting example images from a relevance ranking. Since the top ranked images are all similar, user feedback often results in rearrangement of the presented images only. The Filter Image Browsing method provides better incorporation of user interaction in the retrieval process, because it is based on differences between images rather than similarities. Filter Image Browsing presents overviews of the database to users and lets them iteratively zoom in on parts of the image collection. In contrast to many papers where a new system is just introduced, we performed an extensive evaluation of the methods presented using a user simulation. Results for a database containing 10,000 images show that Filter Image Browsing requires less effort from the user. The implementation of Filter Image Browsing in the ImageRETRO system is accessible via the Web.