ImageCube: A Browser for Image Collections Associated with Multi-dimensional Datasets

Image browsing techniques thus become increasingly important for overview and retrieval of particular images in large-scale collections. At the same time, there are various sets of images which are associated with multi-dimensional or multivariate datasets. We believe that image browsing for such datasets should be inspired from multi-dimensional data visualization techniques. This paper presents Image Cube, a scatter plot-like browser for image collections associated with multi-dimensional datasets. Image Cube locates a set of images into a display space assigning a pair of dimensions to X- and Y-axes. It suggests preferable pairs of dimensions by applying Kendall´s rank correlation and Entropy on the display space, so that users can easily obtain interesting visualization results. This paper presents a case scenario that a user finds a preferable car from an image collection by using Image Cube.