@article{oai:teapot.lib.ocha.ac.jp:00034584,
 author = {Zheng, Yunzhu and Gomi, Ai and Itoh, Takayuki},
 issue = {2},
 journal = {お茶の水女子大學自然科學報告},
 month = {Mar},
 note = {application/pdf, 紀要論文, Image browsing techniques 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 ImageCube, a scatterplot-like browser for image collections associated with multi-dimensional datasets. ImageCube 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 ImageCube.},
 pages = {21--32},
 title = {ImageCube: An Image Browser Featuring a Multi-Dimensional Data Visualization},
 volume = {64},
 year = {2013}
}