We propose a novel high dynamic range (HDR) imaging algorithm for the scenes that contain an extremely wide range of scene radiance. In the HDR imaging, several images are taken under different exposures. Those images usually have displacement from one another due to camera and/or object motions. The challenge of the super HDR imaging is to align those images because any image contains "lost" regions where texture information is completely lost due to overexposure or underexposure. We propose an image alignment algorithm based on similarities of region shapes instead of the similarities of the textures. Experimental comparisons demonstrate that the proposed algorithm outperforms state-of-the-art algorithms.

The anomalies of power equipment can be founded using temperature changes compared to its normal state. In this paper we present a system for visualizing temperature changes in a scene using a thermal 3D model. Our approach is based on two precomputed 3D models of the target scene achieved with a RGB-D camera coupled with the thermal camera. The first model contains the RGB information, while the second one contains the thermal information. For comparing the status of the temperature between the model and the current time, we accurately estimate the pose of the camera by finding keypoint correspondences between the current view and the RGB 3D model. Knowing the pose of the camera, we are then able to compare the thermal 3D model with the current status of the temperature from any viewpoint.

This paper presents an instructional support system based on augmented reality (AR). This system helps a user to work intuitively by overlaying visual information in the same way of a navigation system. In usual AR systems, the contents to be overlaid onto real space are created with 3D Computer Graphics. In most cases, such contents are newly created according to applications. However, there are many 2D videos that show how to take apart or build electric appliances and PCs, how to cook, etc. Therefore, our system employs such existing 2D videos as instructional videos. By transforming an instructional video to display, according to the user's view, and by overlaying the video onto the user's view space, the proposed system intuitively provides the user with visual guidance. In order to avoid the problem that the display of the instructional video and the user's view may be visually confused, we add various visual effects to the instructional video, such as transparency and enhancement of contours. By dividing the instructional video into sections according to the operations to be carried out in order to complete a certain task, we ensure that the user can interactively move to the next step in the instructional video after a certain operation is completed. Therefore, the user can carry on with the task at his/her own pace. In the usability test, users evaluated the use of the instructional video in our system through two tasks: a task involving building blocks and an origami task. As a result, we found that a user's visibility improves when the instructional video is transformed to display according to his/her view. Further, for the evaluation of visual effects, we can classify these effects according to the task and obtain the guideline for the use of our system as an instructional support system for performing various other tasks.

Observation strategy and Digital Electronics unit of Japanese Planet-C, next Japanese Venus observation program is described and the adoptability of loss-lees data compression method, HIREW and JEPG2000 is discussed.

This paper presents a fast lossless image compression method for space and satellite images. The method, which we call HIREW, is based on hierarchical interpolating prediction and adaptive Golomb-Rice coding, and achieves 7-35 times faster compression than existing methods such as JPEG2000 and JPEG-LS, at similar compression ratios. Additionally, unlike JPEG-LS, it supports additional features such as progressive decompression using resolution scaling. An implementation of this codec will be used in the Japan Aerospace Exploration Agency (JAXA)'s Venus Climate Orbiter mission (PLANET-C).

We propose a new technology called the camera-typing interface, which can read printed characters such as URLs with a low-resolution camera. It realizes a type of ubiquitous information service using smart phones with cameras. This method includes two main advantages: automatic concatenation of sequential shots and automatic error correction by re-shooting. The automatic concatenation enables a user to take segmented images of a character string, thus a low-resolution camera can be used as the interface device. The automatic error correction enables the user to correct misrecognized characters just by retaking images around them, providing an easy and natural way of error correction. We present two experimental results to prove effectiveness of our method. Both results indicate that our proposed method is helpful.

We propose a maximum-likelihood approach to segmentation-based recognition of unconstrained handwriting text. The segmentation scores and recognition scores are transformed into posterior probabilities, and the likelihood function which is composed of both these probabilities and character n-gram probabilities is derived from the Bayesian theorem. The recognition result which maximizes the function can be obtained by Viterbi search. Experiments have shown that the proposed likelihood function is effective in the recognition of online Japanese text.

Document clustering is a powerful tool for browsing throughout a document database. Similar documents are gathered into several clusters and a representative document of each cluster is shown to users. To make users infer the content of the database from several representatives, the documents must be separated into tight clusters, in which documents are connected with high similarities. At the same time, clustering must be fast for user interaction. We propose an O(n/sup 2/) time, O(n) space cluster extraction method. It is faster than the ordinal clustering methods, and its clusters compare favorably with those produced by Complete Link for tightness. When we deal with OCR-ed documents, term loss caused by recognition faults can change similarities between documents. We also examined the effect of recognition faults to the performance of document clustering.

The authors have implemented a document image retrieval system; it automatically stores document images in the form of character candidates obtained by character recognition process. When we give some keywords to the system, it can retrieve the images containing at least one of the keywords. The strategy of using character candidates remarkably lowers the rate of missing the keywords on retrieval, because it includes several hypotheses in character segmentation and in character recognition. For finding the keywords from the storage of the character candidates, the authors have developed a fast and efficient searching algorithm. It is able to locate all occurrences of any finite number of keywords in the character candidates. The improvement of using character candidates and the efficiency of the searching algorithm are also described.>