The reflection phenomenon exhibited by highly reflective surfaces considerably affects the quality of captured images, thereby rendering the task of structured light (SL) 3D reconstruction. In this paper, a polarized SL method is proposed to address the reconstruction issues on high-reflectance surfaces. The SL system we build in this paper involves a four-channel polarizing camera and a digital light processing (DLP) projector equipped with a polarizer in the lens. The built system enables the simultaneous acquisition of four groups of fringe images, each with different brightness differences. Then, a binary time-multiplexing SL method is adopted to obtain four distinct point clouds. Additionally, a fusion algorithm is proposed to merge the four point clouds into a single, precise, and complete point cloud. Several experiments have been conducted to demonstrate that the proposed method is capable of achieving excellent reconstruction outcomes on highly reflective surfaces.

Registration of 3D point clouds is an important issue in 3D scanning domain. In this work, we developed a turntable-base structured light system for the automatically 3ED scanning purpose. To realize the fully automatically 3D point clouds registration, a planar surface is placed on the turntable and scanned with different rotation angles. The turntable axis direction vector is calculated by averaging the intersection lines of the reconstructed planes firstly. And the linear minimization function is constructed for the robust and accurate estimation of the turntable origin. A variety of objects are used in the experiment. And the results show that, point clouds under different scanning angles can be precisely registered. In addition, there are no iterative procedures in the proposed algorithm, and that makes the registration procedure more efficiently.

3D real-time acquisition plays a vital role in computer graphics and computer vision. In this paper, we present a dynamic IR structured light sensing system with high resolution and accuracy for real-time 3D scanning. We adopt the Gray code combined with stripe shifting as our 3D acquisition’s coding strategy and parallelize the algorithm via the GPU in our IR 3D scanning system. Our built-up system can capture dense and high-precision 3D model sequences with a speed of 29 Hz. Furthermore, we propose a practical calibration method to obtain accurate calibration parameters for our system. Finally, various experiments are performed to verify the feasibility and accuracy of our proposed IR structured light sensing system.

3D facial expression dataset plays an essential role in computer vision and computer graphics, especially to the data-driven machine learning algorithms like deep-learning etc. In contrast with traditional low-resolution and low-accuracy 3D face related datasets, an accurate and dense facial expression database was introduced in this paper. During the period from January to June 2019, we have collected 8,000 3D facial expression models and 32,000 texture images from 500 subjects. The 3D facial capture device works based on structured light principle. The procedure of 3D face capture and property of 3D samples are introduced in details. The proposed high-accuracy 3D face dataset can be used in many 3D applications, like recognition, animation, and 3D facial expression simulations.