In this paper, we propose an active scanning system using multiple projectors and cameras to acquire a dense entire shape of the object with a single scan (a.k.a. oneshot scan). One of the potential application of the system is to capture a moving object with high frame-rate. Since the pattern used for oneshot scan is usually complicated and those patterns interfere each other if they are projected on the same object, it is difficult to use multiple sets of them for entire shape acquisition. In addition, at the end of the closed loop, errors on each scan are accumulated, resulting in large gaps between shapes. To solve the problem, we propose a oneshot shape reconstruction method using a projector projecting a static pattern of parallel lines with one or two colors. Since each projector projects just parallel lines with a small number of colors, those patterns are easily decomposed and detected even if those patterns are projected multiple times on the same object. We also propose a kind of multi-view reconstruction algorithm for the proposed projector-camera system. In the experiment, we actually built a system which consists of six projectors and six cameras and dense shapes of entire objects were successfully reconstructed.

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Traditional approaches for the screening of cognitive function are often based on paper tests, such as Mini-Mental State Examination (MMSE), that evaluate the degree of cognitive impairment and provide a score of patient’s mental ability. Procedures for conducting paper tests require time investment involving a questioner and not suitable to be carried out frequently. Previous studies showed that dementia impaired patients are not capable of multi-tasking efficiently. Based on this observation an automated system utilizing Kinect device for collecting primarily patient’s gait data who carry out locomotion and calculus tasks individually (i.e., single-tasks) and then simultaneously (i.e., dual-task) was introduced. We installed this system in three elderly facilities and collected 10,833 behavior data from 90 subjects. We conducted analyses of the acquired information extracting 12 features of single- and dual-task performance developed a method for automatic dementia score estimation to investigate determined which characteristics are the most important. In result, a machine learning algorithm using single and dual-task performance classified subjects with an MMSE score of 23 or lower with a recall 0.753 and a specificity 0.799. We found the gait characteristics were important features in the score estimation, and referring to both single and dual-task features was effective.

In the present paper, we propose a one-shot scanning system consisting of multiple projectors and cameras for dense entire shape acquisition of a moving object. One potential application of the proposed system is to capture a moving object at a high frame rate. Since the patterns used for one-shot scanning are usually complicated, and the patterns interfere with each other if they are projected onto the same object, it is difficult to use multiple sets of patterns for entire shape acquisition. In addition, the overlapped areas of each object have gaps and errors are accumulated. As such, merged shapes are usually noisy and inconsistent. In order to address this problem, we propose a one-shot shape reconstruction method using a projector to project a static pattern of parallel lines of one or two colors. Since each projector projects only parallel lines with a small number of colors, these patterns are easily decomposed and detected even if the patterns are projected multiple times onto the same object. We also propose a multi-view reconstruction algorithm for the projector-camera system. In the experiment, we built a system consisting of six projectors and six cameras, and dense shapes of entire objects were successfully reconstructed.

Recently, several method have been proposed to capture 3D shapes of a moving object at a high frame rate. One of promising approach to reconstruct a 3D shape is a projector-camera system that projects structured light pattern. One of the problem of this approach is that it has difficulty to obtain texture simultaneously because the texture is interfered by the illumination from the projector. The system proposed in this paper overcomes this issue by separating the light wavelength for texture and shape. The pattern is projected by using infrared light and the texture is captured by using visible light. If the cameras for infrared and visible lights are placed at different position, it causes the misalignment between texture and shape, which degrades the quality of the textured 3D model. Therefore, we developed a multi-band camera that acquires both visible and infrared lights from a single viewpoint. Moreover, to reconstruct a 3D shape using multiple wavelengths of light, namely multiple colors, an infrared pattern projector is developed to generate a multi-band grid pattern. Additionally, a simple method to calibrate the system is proposed by using a fixed grid pattern. Finally, we show the textured 3D shapes captured by the experimental system.