We propose a practical 3D method for measuring translucent objects with high accuracy. We improve the accuracy of the measurement by a high-frequency dashed line projection to a target object, which eliminates the influence of subsurface scattering while maintaining higher image contrast. For efficient measurement, multiple dashed lines are projected at the same time and we identify them without error by a proposed complementary Gray code, thus reducing the number of projections to less than 1/10 of that by conventional light sheet scanning. With regard to performance, we show that the frequency of the dashed line largely determines the accuracy and that there is a trade off between depth offset as a systematic error and random error. We validate the proposed method by measuring both canonical translucent samples with various translucencies and actual engineering parts.

Global illumination effects such as inter-reflections and subsurface scattering result in systematic, and often significant errors in scene recovery using active illumination. Recently, it was shown that the direct and global components could be separated efficiently for a scene illuminated with a single light source. In this paper, we study the problem of direct-global separation for multiple light sources. We derive a theoretical lower bound for the number of required images, and propose a multiplexed illumination scheme which achieves this lower bound. We analyze the signal-to-noise ratio (SNR) characteristics of the proposed illumination multiplexing method in the context of direct-global separation. We apply our method to several scene recovery techniques requiring multiple light sources, including shape from shading, structured light 3D scanning, photometric stereo, and reflectance estimation. Both simulation and experimental results show that the proposed method can accurately recover scene information with fewer images compared to sequentially separating direct-global components for each light source.

By using a state observer, a new robust trajectory tracking control scheme is developed in this paper for electrically driven robot manipulators. The role of the observer is to estimate joint angular velocities. The proposed controller does not employ adaptation, but assures robust stability of tracking error between joint angles and desired trajectories. At sacrificing asymptotical stability of the tracking errors, the configuration of the proposed controller becomes very simple, compared with regressor-based adaptive controllers. It is shown in the closed-loop system using the proposed controller that the Euclidian norm of tracking errors arrives at any small closed region with any convergent rate by setting only one design parameter. Especially for the desired trajectories converging to constant ultimate values, it is assured that tracking errors converge to zero.

We propose a linear algorithm that is useful for realizing geometric registration between the view of a real scene and that of a virtual object in an image-based rendering framework. In a unified framework, the novel view synthesis of a virtual object based on three views' matching constraints and the recovery of the camera pose that is necessary for the base image selection can be performed. The feasibility of the algorithm is demonstrated by using ground-truth synthesized data and real scene data.