Most opals used as gemstones have an optical effect–’play of color’, to produce rainbowcolored patterns. While most of gemstones, such as diamond, ruby, and sapphire, are classified as monocrystal or polycrystal materials, opal is classified as amorphous materials with a complex internal structure. Therefore, visual simulation modeling of opal requires a necessary and sufficient spatial scale under the constraints of computational resources. In this study, we propose a new method for modeling the internal structure of opal using three-dimensional Voronoi tessellation, which enables us to simulate play of color based on crystallography. By focusing on the characteristics of the three-dimensional Voronoi diagram, we reduce space complexity significantly compared to existing studies. Furthermore, we show that it is possible to model a variety of opal using four parameters: the diameter of particles that make up opal, scattering coefficient and absorption coefficient due to impurities contained within the particles, and the tilt of diffraction grating.

Aortic valve disease, one of the cardiac diseases, causes symptoms such as short breath, anginal pain, and heart failure due to valve malfunction. The aortic valve disease needs a surgery, called “aortic valvuloplasty”, which rarely causes the postoperative thrombogenesis and requires no medication. The surgery, however, is very difficult and requires preoperative planning and simulations. In this paper, we propose a particle based simulation using a model generated from X-ray CT data. In the simulation, blood flow from the left ventricle to the aorta is visualized, and the pressure changes in the aorta and the left ventricle are compared with those in the real data. After the left ventricle contracts, the aortic valve opens, the blood flows from the left ventricle to the aorta, and the left ventricular pressure increases. As the blood is ejected from the left ventricle to the aorta, the aortic pressure rises. Then, as the left ventricle relaxes, the left ventricular pressure decreases below the aortic pressure, and the aortic valve closes. As the result of the simulation considering the interplay between the left ventricle’s contraction and relaxation, and the valve’s opening and closing, we have confirmed that the pressure changes in the aorta and the left ventricle have become very similar to the real data.

Rendering with global illumination has been used mainly in the field of film production thanks to its highly photorealistic image synthesis. When using Monte Carlo raytracing, which is one of the major rendering methods, the resulting images may contain some points that deviate significantly from final convergence values. It is needed to generate output images with a small number of samples and low variance by improving the variance reduction per sample. Path guiding is a method for reducing such variance by using importance sampling of the estimated radiance distribution in advance to construct efficient paths. However, in many-light scenes, estimating radiance distribution may be slow due to the complexity of distribution obtained by the light sources and it could make variance rather increased by constructing paths from the trained distribution of low accuracy. In this paper, therefore, we propose a method for accelerating the computational efficiency of path guiding with many-light global illumination by sophisticating light source sampling to better estimate radiance distribution. The proposed method was implemented as a GPU program, and we empirically proved that it reduced up to 46.8% of variance compared to the normal path tracing.

In recent years, with the rapid spread of smart devices, biometric authentication technology has been widely used as a user authentication method for security and privacy protection, with advantages such as prevention of forgetting and impersonation, and reduction of authentication time. However, there are some problems, such as the decrease in reliability due to changes in the usage environment and unauthorized use of the device after authentication. Therefore, biometric authentication methods with usage environment recognition and continuous authentication have been proposed as a solution to this problem. In this paper, we focused on the limitations of available resources on the smart device and the reduced convenience of enrolling and updating templates. We propose a method of selecting a biometric modality that balances authentication accuracy and resource consumption, and a method of automatically enrolling and updating templates, and report the results of evaluating their effectiveness.

A 3D point cloud is a representation of a 3D space with a large number of discrete coordinate

data obtained by laser or photogrammetric surveying. The processing of 3D point clouds enables us

to directly analyze features in 3D space, which is expected to have various applications. A contour tracking

method for 3D point clouds has been proposed by Daniel et al. This method is intended for surface

segmentation and surface meshing, and performs surface fitting on a set of 3D points that show geometric

shapes, and traces contours on a set of points projected on the edges that exist at the boundaries between

surfaces. However, this method is not necessarily suitable for contour tracking of edges of 3D point clouds

that represent general natural shapes, such as those obtained at surveying sites. In this work, we propose

a new method of contour tracking for edges of 3D point clouds representing natural shapes, and show its

effectiveness on drawing map of the remains through experiments on actual remain data.

Ina City, Nagano Prefecture, has established an open-air vegetable consortium to develop an asparagus harvester in order to establish a smart agriculture model utilizing advanced equipment. This paper introduces the overall system of the asparagus harvester and describes the asparagus recognition process, which is the core technology of the asparagus harvester. Point cloud is obtained from depth image using a depth camera, and asparagus are clustered based on the point cloud information. To cut the asparagus accurately, the boundary between the asparagus and the soil is recognized, and the asparagus is cut, gripped, and harvested using a robot. Because of the outdoor location, the point cloud is often interrupted, while the point cloud can become integrated with neighboring asparagus. We describe a simple method for improving these problems and show the results of a test in an actual field.

Non-Photorealistic Rendering (NPR) has been carried out actively to generate non-photorealistic rendered images such as painterly or illustrative style images. A method using Scalable Poisson Disk Sampling that can generate various painterly style image has been proposed. However, it required long computational time. In this paper, we propose Random Disk Paving method, a fast sampling method by paving disks with random radii. Several experimental results showed that Random Disk Paving method can place disks with random radii at fast and at random, but uniformly. We applied Random Disk Paving method to painterly style image generation method and the results show that the our method can generate various painterly style images up to 40 times faster than the conventional method, and the generated images are finer. These results show our proposed method is useful and effective.