[in Japanese]

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[in Japanese]

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We have developed a similarity-based image retrieval system that represents retrieved images as a scatter diagram a semantic space. One axis of the space shows the suitability of a keyword assigned to each image. The suitabilities are estimated by linearly transforming the image features of the retrieved data, and the coefficients of the transformation are determined by multiple regression analysis. First, a-user selects images as key images. Then the system retrieves images and calculates the estimated suitablities variance among the retrieved images for each keyword, and presents the user keywords that give the large variances. Next, the user selects a keyword from the given keywords for each axis. Finally, the system displays the retrieved images in the semantic space spanned by the two axes. The system enables the user to apply the center of gravity among the features of the key images to the retrieval. The system thus effectively assists the user in retrieving images by integrating the semantic visualization and the center of gravity retrieval. Testing of the keyword suitability estimation showed that the estimation precision became high by using keywords with the large suitabilites variances.

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A visualization method is presented for data represented by a graph partitioned into fuzzy clusters. The data are arranged in a two-or three-dimensional space by correspondence analysis based on the memberships of the data in the obtained clusters. Data related by their links are represented by a directed graph or a bipartite undirected one. The fuzzy clusters are then extracted sequentially from the data based on this graph representation. At each stage of cluster extraction, memberships are calculated by solving an optimization problem using an iterative scheme. The data are then arranged in a two-or a three-dimensional space by correspondence analysis based on the memberships of the data. This data visualization method can be used to recommend movies by visual collaborative filtering and to visualize structures in a software program. It can be extended to more complexly structured data represented by the combination of a directed graph and a bipartite undirected one. This extended method can be used to search for Web pages by keywords and to recommend them as links. For example, the Web can be browsed to find information about sofas and carpets based on the impression they make and to visualy support their coordination.

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An algorithm is described for extracting tree-structure skeletons that are accurate and robust. Volumetric skeletons are needed to accurately measure the length along branching and winding structures. Skeletons are also needed for automatic virtual navigation, such as traveling through human organs to control the movement and orientation of a virtual camera. The proposed algorithm finds the skeleton accurately and rapidly. The solution is automatically obtained, freeing the user from having to engage in preprocessing the data. Accurate skeletons were computed on a number of test datasets, and t he algorithm was demonstrated to be efficient with running times of below five minutes.

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Particle models have been used for computer animation of cloth fabrication, although the relation with the mechanical properties of cloth is not clear. In particular, the non-linearity and anisotropy of the mechanical properties are important. A particle model reflecting these properties is described. The precise collision and repulsion mechanism is represented in the particle model by integrating the rigid body model and the particle model. The proposed model was shown to be valid by comparing the results of experiments and simulation using different cloth materials.

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An array antenna, which has a large number of radiating element, is divided into subarrays. The current distribution of the antenna is approximated as a Taylor distribution using the genetic algorithm to combine subarrays having the same current distribution. Doing this simplifies the feed systems. By considering the array antenna as an aggregate of subarrays, designs, production, inspection, and maintenance are simplified, which in turn reduces costs.

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Charge-modulation-device (CMD) image sensors feature non-destructive readout and high-speed operation. By using the source-reset method in the CMD reset operations, it is possible to control the reset of the pixel-accumulated charge from outside the sensor. Making use of these features, we propose a subject-adaptive-type wide-dynamic-range imaging system that increases the dynamic range of the CMD by activating the electronic shutter only for areas having strong incident light. This prevents the sensor from becoming saturated. The advantage of this system is that there is no need to modify the conventional CMD structure to increase the dynamic range-only a simple circuit need be added outside the sensor. Experiment on this system was performed using such CMDs as line and two-dimensional sensors, and the dynamic range was increased twice as much.

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[in Japanese]

View full abstract

[in Japanese]

View full abstract