High-speed display of 3-D objects in virtual reality environments is one of the currently important subjects. Shape simplification is considered an efficient method. This paper presents a method of hierarchical cube-based segmentation for shape simplification and multiresolution model construction. The relations among shape simplification, resolution and visual distance are derived firstly. The first level model is generated from scattered range data by cube-base segmentation with the first level cube size. Multiresolution models are then generated by re-sampling polygonal patch vertices of each former level model with hierarchical cube-based segmentation structure. The results show that the algorithm is efficient for constructing multiresolution models of free-form shape 3-D objects from scattered range data and high compression ratio can be obtained with little noticeable difference during the visualization.

Photovoltaic devices capable of generating more than 200 volts with an area of 1 cm2 have been developed for directly driving microactuators such as piezoelectric or electrostatic actuators. The micro-devices interconnect 285 micro cells (unit cell size: about 0.5 mm 2.0 mm) in series, and have an open circuit voltage (Voc) of 207 volts, a short circuit current (Isc) of 36.6 µA, a maximum output power (Pmax) of 4.65 mW and a fill factor (F.F.) of 0.615 under AM (Air Mass) 1.5 and 100 mW/cm2 illumination. This voltage is the highest in the world for the area of 1 cm2. The series connection is precisely processed by a focused laser beam, thereby significantly reducing the area needed for device connections. It has been confirmed that a piezoelectric polymer can be directly driven by the electrical output in evaluating the potential of the devices to be used as a microactuator's power source.

The reconstruction of 3-D moving images from transmitted parameters describing position, attitude and shape variation of objects in a virtual 3-D space has been studied as an application of three dimensional (3-D) image communication. The shape information was obtained from a database that was built in advance. Since an appropriate database of 3-D object shapes needs to be developed, efficient storage of the shape data of the actual objects might become a key technology. This paper proposes an efficient entropy coding method of voxel map data obtained with shape measuring equipment. The proposed method converts the voxel map data into an octree and encodes their node information with conditional probability on the state of neighbor nodes sequentially, beginning with the upper hierarchy level. This method has the property of being able to extract information up to a given arbitrary hierarchy level because of its hierarchical characteristic. For implementation, two methods are proposed for reducing the large number of contexts, one uses 3-D isotropism, the other uses sample statistics. The experimental coding results using several sample data sets show that the proposed method can reduce the information volume by about 20% in comparison to the ordinary method using unconditional entropy. The binary voxel map of 512512512 can be represented by approximately 680 kbits.

A new finishing method using an advanced ECM assisted by fine abrasive grains was developed, in order to smooth and finish surfaces of 3-dimensional micro components used in micromachines. With the method, a fine surface of selected micro-area, which is not obtained by micro-EDM nor conventional ECM, was obtained in a few minutes. We also developed an advanced machine which has a performance of making 3-D complicated micro structures with fine surfaces by the combination of micro-EDM and the developed finishing method. The performance is achieved by a sequential process from the micro-EDM to the finishing without handling workpiece. Using the new machine, we obtained a high precision shaft with a mirror-like surface. The result is satisfactory to apply the method to making a cylindrical substrate for a rotor of a micro wobble motor. The machining process combined the micro-EDM and the new finishing will be applied to producing micro components such as mechanical parts, mirrors and molding dies.

In this paper, we propose a camera calibration method that estimates both intrinsic parameters (perspective and distortion) and extrinsic parameters (rotational and translational). All camera parameters can be determined from one or more images of planar pattern consists of parallelogramatic grid points. As far as the pattern can be visible, the relative relations between camera and patterns are arbitrary. So, we have only to prepare a pattern, and take one or more images changing the relative relation between camera and the pattern, arbitrarily; neither solid object of ground truth nor precise z-stage are required. Moreover, constraint conditions that are imposed on rotational parameters are explicitly satisfied; no intermediate parameter that connected several actual camera parameters are used. Taking account of the conflicting fact that the amount of distortion is small in the neighborhood of the image center, and that small image has poor clues of 3-D information, we adopt iterative procedure. The best parameters are searched changing the size and number of parallelograms selected from grid points. The procedure of the iteration is as follows: The perspective parameters are estimated from the shape of parallelogram by nonlinear optimizations. The rotational parameters are calculated from the shape of parallelogram. The translational parameters are estimated from the size of parallelogram by least squares method. Then, the distortion parameters are estimated using all grid points by least squares method. The computer simulation demonstrates the efficiency of the proposed method. And the results of the implementation using real images are also shown.

This paper presents an overview of research activities in Japan in the field of very low bit-rate video coding. Related research based on the concept of "intelligent image coding" started in the mid-1980's. Although this concept originated from the consideration of a new type of image coding, it can also be applied to other interesting applications such as human interface and psychology. On the other hand, since the beginning of the 1990's, research on the improvement of waveform coding has been actively performed to realize very low bit-rate video coding. Key techniques employed here are improvement of motion compensation and adoption of region segmentation. In addition to the above, we propose new concepts of image coding, which have the potential to open up new aspects of image coding, e.g., ideas of interactive image coding, integrated 3-D visual communication and coding of multimedia information considering mutual relationship amongst various media.

The Yasuura method is effective for calculating scattering problems by bodies of revolution. However dealing with 3-D scattering problems, we need to solve bigger size dense matrix equations. One of the methods to solve 3-D scattering is to use multipole expansion which accelerate the convergence rate of solutions on the Yasuura method. We introduce arrays of multipoles and obtain rapidly converging solutions. Therefore we can calculate scattering properties over a relatively wide frequency range and clarify scattering properties such as frequency dependence, shape dependence, and polarization dependence of 3-D scattering from perfectly conducting scatterer. In these numerical results, we keep at least 2 significant figures.

Most research on the estimation of direction of arrival (DOA) has been performed based on the assumption that the signal sources are point sources. In some real surroundings, signal source localization can more adequately be accomplished with distributed source models. When the signal sources are distributed over an area, we cannot directly use well-known DOA estimation methods, because these methods are established based on the point source assumption. In this paper, we propose a 3-dimensional distributed signal source model, in which a source is represented by two parameters, the center angle and degree of dispersion. Then, we address the estimation of the elevation and azimuth angles of distributed sources based on the parametric distributed source modeling in the 3-dimensional space.

In this paper we propose a new medical image processing system called Virtualized Endoscope System (VES)", which can examine the inside of a virtualized human body. The virtualized human body is a 3-D digital image which is taken by such as X-ray CT scanner or MRI scanner. VES consists of three modules; (1) imaging, (2) segmentation and reconstruction and (3) interactive operation. The interactive operation module has following thee major functions; (a) display of, (b) measurement from, and (c) manipulation to the virtualized human body. The user of the system can observe freely both the inside and the outside of a target organ from any point and any direction freely, and can perform necessary measurement interactively concerning angle and length at any time during observation. VES enables to observe repeatedly an area where the real endoscope can not enter without pain from any direction which the real endoscope can not. We applied this system to real 3-D X-ray CT images and obtained good result.

In this paper, we study three-dimensional motion estimation using optical flow. We construct a weighted quotient-form objective function that provides an unbiased estimator. Using this objective function with a certain projection operator as a weight drastically reduces the computational cost for estimation compared with using the maximum likelihood estimator. To reduce the variance of the estimator, we examine the weight, and we show by theoretical evaluations and simulations that, with an appropriate projection function, and when the noise variance is not too small, this objective function provides an estimator whose variance is smaller than that of the maximum likelihood estimator. The use of this projection is based on the knowledge that the depth function has a positive value (i. e., the object is in front of the camera) and that it is generally smooth.

Based on a simple model for the statistical error characteristics of range sensing, a numerical scheme called renormalization is presented for optimally fitting a planar surface to data points obtained by range sensing. The renormalization method has the advantage that not only an optimal fit is computed but also its reliability is automatically evaluated in the form of the covariance matrix. Its effectiveness is demonstrated by numerical simulation. A scheme for visualizing the reliability of computation by means of the primary deviation pair is also presented.

We thought that multiple skeletons were inherent in an ordinary three-dimensional object. A thinning method is developed to extract multiple skeletons using 333 templates for boundary deletion based on the hit or miss transformation and 222 templates for checking one voxel thickness. We prepared twelve sets of deleting templates consisting of total 194 templates and 72 one voxel checking templates. One repetitive iteration using one sequential use of the template sets extracts one skeleton. Some of the skeletons thus obtained are identical; however, multiple independent skeletons are extracted by this method. These skeletons fulfill the well-recognized three conditions for a skeleton. We extracted three skeletons from the cube, two from the space shuttle model and four from the L-shaped figure by Tsao and Fu. The digital medial skeleton, which is not otherwise extracted, is extracted by comparing the multiple skeletons with the digital medial-axis-like-figure. One of our skeletons for the cude agreed with the ideal medial axis. The locations of the gravity center of the multiple skeletons are compared with that of the original shape to evaluate how uniform or non-biased skeletons are extracted. For the L-shaped figure, one of our skeletons is found to be most desirable from the medial and uniform points of view.

Theoretically, corresponding pairs of feature points between two stereo images can determine their 3-D locations uniquely by triangulation. In the presence of noise, however, corresponding feature points may not satisfy the epipolar equation exactly, so we must first correct the corresponding pairs so as to satisfy the epipolar equation. In this paper, we present an optimal correction method based on a statistical model of image noise. Our method allows us to evaluate the magnitude of image noise a posteriori and compute the covariance matrix of each of the reconstructed 3-D points. We demonstrate the effectiveness of our method by doing numerical simulation and real-image experiments.

This paper presents a theoretically best algorithm within the framework of our image noise model for reconstructing 3-D from two views when all the feature points are on a planar surface. Pointing out that statistical bias is introduced if the least-squares scheme is used in the presence of image noise, we propose a scheme called renormalization, which automatically removes statistical bias. We also present an optimal correction scheme for canceling the effect of image noise in individual feature points. Finally, we show numerical simulation and confirm the effectiveness of our method.

This paper studies the problem of reconstructing a planar surface from stereo images of multiple feature points that are known to be coplanar in the scene. We present a direct method by applying maximum likelihood estimation based on a statistical model of image noise. The significant fact about our method is that not only the 3-D position of the surface is reconstructed accurately but its reliability is also computed quantitatively. The effectiveness of our method is demonstrated by doing numerical simulation.

This paper presents a new microprocessing method that uses a Cl2 fast atom beam (FAB) with stainless steel (SUS304) patterned masks. This new method uses the patterned mask instead of lithographically processed patterned photoresist materials employed in the conventional FAB microprocessing method. We examined the performance of this method by etching GaAs workpieces under various conditions: (1) by setting the distance between the mask surface and flat workpiece surface, L, from 0 µm to 500 µm; (2) by setting the angle between the FAB axis and the flat workpiece surface, θ; to either 30or 50. (3) by etching a workpiece surface that had a 15-µm step and two different surface textures, smooty and undulated; and (4) by doing overlapped etching using a square-patterned mask first and then a circular-patterned mask. The experiments show that the accuracy of reproducing the mask pattern on the etched surface increases with decreasing L. Moreover, the etching rate is almost the same (L100 µm) and decreases slightly at longer distance (L100 µm). The experiments also show that the side walls of the surface are parallel to the FAB axis, even for θ0, indicating that anisotropic etching can be achieved. The experiments for the stepped surface with different surface textures show the surface texture is not affected by the FAB etching. The overlapped etching experiments show that FAB etching is capable of producing overlapped structures. These results demonstrate that this new FAB method can be used in the microproduction of multi-faced, overlapped, three-dimensional microstructures.

A single-chip architecture for three-dimensional (3-D) computer graphics (CG) is discussed assuming portable equipment with a 3-D CG interface. Based on a discussion of chip requirements, an architecture utilizing DRAM technology is proposed. A 31-Mbit, on-chip DRAM cell array allows a full-color, 480640-pixel frame with two 3-D frame buffers for double buffering and one 2-D frame buffer for superimposed or background images. The on-chip pixel generator produces R, G, B, and Z data in a triangular polygon with a zigzag-scan interpolation algorithm. The on-chip frame synthesizer combines data from one of the 3-D buffers with that from the 2-D buffer to produce superimposed or background 2-D images within a 3-D CG image. Parallel alpha-blending and Z-comparison circuits attached to the DRAM cell array provide a high data I/O rate. Estimation of the chip performance assuming the 0.35-µm CMOS design rule shows the chip size, the drawing speed, on-chip data I/O rate, and power dissipation would be 1413.5-mm, 0.25 million polygons/s, 1 gigabyte/s, and 590 mW at a voltage of 3.3 V, respectively. Based on circuit simulations, the chip can run on a 1.5-V dry cell with a drawing speed of 0.125 million polygons/s and a power dissipation of 61 mW. A scaled-down version of the chip which has an 1-kbit DRAM cell array with an attached alpha-blending circuit is being fabricated for evaluation.

Introducing a general statistical model of image noise, we present an optimal algorithm for computing 3-D motion from two views without involving numerical search: () the essential matrix is computed by a scheme called renormalization; () the decomposability condition is optimally imposed on it so that it exactly decomposes into motion parameters; () image feature points are optimally corrected so that they define their 3-D depths. Our scheme not only produces a statistically optimal solution but also evaluates the reliability of the computed motion parameters and reconstructed points in quantitative terms.

This paper describes a noise resistant algorithm for estimating 3-D rigid motion from optical flow. We first discuss the problem of constructing the objective function to be minimized. If a Gaussian distribution is assumed for the niose, it is well-known that the least-squares minimization becomes the maximum likelihood estimation. However, the use of this objective function makes the minimization procedure more expensive because the program has to go through all the points in the image at each iteration. We therefore introduce an objective function that provides unbiased estimators. Using this function reduces computational costs. Furthermore, since good approximations can be analytically obtained for the function, using them as an initial guess we can apply an iterative minimization method to the function, which is expected to be stable. The effectiveness of this method is demonstrated by computer simulation.

This paper is concerned with the data compression and interpolation of multi-view image set. In this paper, we propose a novel disparity compensation scheme based on geometric relationship. We first investigate the geometric relationship between a point in the object space and its projection onto view images. Then, we propose the disparity compensation scheme which utilize the geometric constraints between view images. This scheme is used to compress the multi-view image into the structure of the triangular patches and the texture data on the surface of patches. This scheme not only compresses the multi-view image but also synthesize the view images from any viewpoints in the viewing zone. Also, this scheme is fast and have compatibility with 2-D interframe coding. Finally, we report the experiment, where two sets multi-view image were used as original images and the amount of data was reduced to 1/19 and 1/20 with SNR 34 dB and 20 dB, respectively.