Multilinearization data structure for image browsing

Image search has been actively studied in recent years. On the other hands, image browsing has received little attention. Image browsing refers to the process of presenting some forms of overview or summary of the image relationships, thus facilitating a user to navigate across the data set and find images of interests. In this paper, we present a new data structure built on the multi-linearization of image attributes for efficient organization of the data set and fast visual browsing of the images. We describe new techniques for multi-linearization based on multiple space-filling curves and hierarchical clustering techniques. In addition to providing fast navigation, our proposed data structure allows computationally efficient insertion and deletion of images from the data set. We then present a novel image navigator and browser built on dual-linearization data structure and intuitive presentation of image relevance and relationships, demonstrate the image navigation process, and report results on 1000 and 22,000 image databases. We also discuss how our data structure can be extended to support fast image search.