Visual Clustering of Image Search Results

This paper presents a novel method for visualizing the results of an image search. Current approaches to visualizing WWW image searches tank results in a linear list and present them as a sorted thumbnail grid. The method outlined in this paper visually clusters images based on the user's search terms. To accomplish this, a flexible image retrieval method which incorporates a combination of content-based and textual image matching is used. A new information visualization is used to display the search results. In our model multiple types of partitioning and querying can occur concurrently, thereby creating a multi-dimensional display of image properties. The display groups similar images, enabling users to quickly scan for the most relevant images. This visualization allows users to exploit the location of images as their guide to what an image contains and use thumbnails to preview potentially relevant images. Through the identification of relevant images users can locate relevant areas in the visualizat ion. It is then possible for users to focus their attention on one area of the visualization using a zooming function. The user's interaction with the system is explored using new evaluation metrics based on Information Foraging theory