The recent revolution of digital camera technology has resulted in much larger collections of images. Image browsing techniques thus become increasingly important for overview and retrieval of images in sizable collections. This paper proposes CAT (Clustered Album Thumbnail), a technique for browsing large image collections, and its interface for… (More)
Figure 1. Overview of comp-i virtual space visualizing the introduction of " Valse des fleurs " (16 channels, 101 subsections).
Occlusion is an important problem to be solved for readability improvement of 3D visualization techniques. This paper presents an occlusion reduction technique for cityscape-style 3D visualization techniques. The paper first presents an algorithm for occlusion reduction. It generates bounding boxes of 3D objects on the 2D display space, moves them to reduce… (More)
Information visualization techniques are useful to overlook large-scale information stored in computers, or interactively retrieve required information. We have presented " HeiankyoView " , a technique for large-scale hierarchical data visualization, and its various applications. This paper presents various application of musical information visualization… (More)
CAT Summary This thesis proposes CAT (Clustered Album Thumbnail), a technique for clus-teringand browsing large number of images. It also provides a user interface for controlling the level of details. As a preprocessing, CAT first hierarchically clusters images and selects representative images for each cluster. And then, CAT visualizes the tree structure… (More)
We propose a 3D visualization technique which realizes browsing of hierarchical or metadata-based link structures intelligibly while avoiding 3D cluttering. The poster describes the algorithm which relocates the metaphor of contents mapped onto a 3D space so that cluttering is avoided on a 2D projection space. We apply the vi-sualization technique "… (More)
Previously we have presented CAT (Clustered Album Thumbnail), a technique for browsing large image collections, and its interface for controlling the level of details (LOD). CAT applies tree-structured clustering to images based on their keywords and pixel values, and selects representative images for each cluster. A hierarchical data visualization… (More)