[in Japanese]

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[in Japanese]

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We propose a distributed automatic method of calibrating cameras for multiple-camera-based vision systems. because manual calibration is a difficult and time-consuming task. However, the data size and computational costs of automatic calibration increase when the number of cameras is increased. We solved these problems by employing a distributed algorithm. With our method, each camera estimates its position and orientation through local computation using observations shared with neighboring cameras. We formulated our method with two kinds of geometrical constraints, an essential matrix and homography. We applied the latter formulation to a human tracking system to demonstrate the effectiveness of our method.

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Depression is becoming a major problem. It is necessary to identify minor depression and melancholy in the early detection of depression. Evaluation by a psychiatrist is needed for an accurate diagnosis. However, there is problem with the shortage of psychiatrists. Therefore, a self-rating scale has been used for screening purposes before the psychiatrist's diagnosis. However, its results have often been unreliable. Consequently, we propose a simple means of detecting depression through the recognition of facial expressions, which produces reliable results. Furthermore, we evaluate this test for mobile screening.

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Many systems to aid communication have been developed for seriously physically handicapped people such as ALS patients. The eye-gaze input system is currently being evaluated as a novel interface; it can be used to operate a computer with eye movement only. Most conventional eye-gaze input systems use of an infrared ray on the eyes to detect eye-gaze. However, prolonged irradiation could damage the eyes. This paper proposes a new eye-gaze input system with multi-indicators utilizing a personal computer and a home video camera to detect eye-gaze under natural light. It detects both vertical and horizontal eye-gaze through simple image analysis, and does not require special image processing units or sensors. It also compensates for measurement errors caused by head movement, i.e., it can detect eye-gaze with a high degree of accuracy. Therefore, it is capable distinguishing many indicators and its applications are expected to be expanded.

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Our fringe printer for printing digitally synthetic holograms, which we reported in a previous article, was improved to increase its stability and resolution. The old model was capable of printing elliptical dots in a diameter of 2×4 μm by focusing the beam of a laser diode onto a hologram dry plate. However, active control to focus the laser beam was not taken into account in the design, and therefore, the resolution and the stability were limited. The new fringe printer has had mechanisms incorporated to detect surface undulations in the recording materials and control the beam waist only on the surface. These improvements made it possible to reduce the dot size to 1.5×3 μm and to keep the dots size within a large area.

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A display system that does not require the use of special glasses is a useful technology in 3D imaging. Conventional lenticular and parallax barrier display systems have disadvantages such as pseudoscopic images. This report describes the development of a stereoscopic display using a parallax polarizer barrier to eliminate the pseudoscopic viewing area. This 3D display can solve the pseudoscopic image problem and enables multiple observers to view 3D images without the need for special glasses.

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We previously presented a method of selectively sharpening monochrome images. The algorithm in our method is based on the coupled nonlinear diffusion process composed of a nonlinear diffusion term, a fidelity term, and an overshooting term, and can sharpen blurred edges without increasing noise visibility. This paper extends our algorithm to selectively sharpening color images. We take into accounts two schemes to treat the three primary color components in finding out how to extend it. Through quantitative experiments, we evaluate selective sharpening performance achievable with the two schemes. Of the two schemes, which are based on the coupled nonlinear diffusion process, collectively treating the three primary color components achieves better performance than treating them independently, yet both two schemes can sharpen blurred color edges more selectively than the existing adaptive peaking method, which is a typical means of enhancing sharpness.

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We demonstrate the basic performance of a high S/N ratio CMOS image sensor with a real-time object-categorizing function. The sensor has capabilities of converting all pixels from analog to digital, object separation, and video image capture. The image sensor is expected to be utilized in the communication and storage application fields offering high quality and large volume image data.

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