Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

A phase unwrapping algorithm specially designed for the phase-shifting fringe projection profilometry (FPP) is proposed. It combines a revised dual-frequency fringe projectionalgorithm and a proposed fringe background based quality guided phase unwrapping algorithm (FB-QGPUA). Phase demodulated from the high-frequency fringe patterns is partially unwrapped by that demodulated from the low-frequency ones. Then FB-QGPUA is adopted to further unwrap the partially unwrapped phase. Influences of the phase error on the measurement are researched. Strategy to select the fringe pitch is given. Experiments demonstrate that the proposed method is very robust and efficient.

High-accuracy 3D measurement based on binocular vision system is heavily dependent on the accurate calibration of two rigidly-fixed cameras. In most traditional calibration methods, stereo parameters are iteratively optimized through the forward imaging process (FIP). However, the results can only guarantee the minimal 2D pixel errors, but not the minimal 3D reconstruction errors. To address this problem, a simple method to calibrate a stereo rig based on the backward projection process (BPP) is proposed. The position of a spatial point can be determined separately from each camera by planar constraints provided by the planar pattern target. Then combined with pre-defined spatial points, intrinsic and extrinsic parameters of the stereo-rig can be optimized by minimizing the total 3D errors of both left and right cameras. An extensive performance study for the method in the presence of image noise and lens distortions is implemented. Experiments conducted on synthetic and real data demonstrate the accuracy and robustness of the proposed method.

The electronic properties of monolayer (ML) Ga2O3 and transport properties of ML Ga2O3-based n-type metal–oxide–semiconductor field-effect transistors (MOSFETs) are investigated by first-principles calculations under the framework of density functional theory (DFT) coupled with the nonequilibrium Green’s function (NEGF) formalism. The results show that ML Ga2O3 has a quasi-direct band gap of 4.92 eV, and the x- and y-directed electron mobilities are 1210 and 816 cm2 V–1 s–1 at 300 K, respectively, under the full consideration of phonon scattering. The electron–phonon scattering mechanism shows a temperature-dependent behavior, with the acoustic modes dominating below 300 K and optical modes dominating above 300 K. At a gate length of L g = 5 nm, the on-current of ML Ga2O3 n-MOSFET for high-performance (HP) application is 2890 μA/μm, which is more than those of the most reported two-dimensional (2D) materials. The delay time as well as the power delay product of ML Ga2O3 MOSFETs can meet the demands of the latest International Technology Roadmap for Semiconductors (ITRS) for HP and low-power (LP) applications until L g is less than 4 and 5 nm, respectively. Through underlap structure and doping optimization strategies, ML Ga2O3 n-MOSFET can further fulfill the ITRS requirements for 1 nm. At last, we compare the performance of the 32-bit arithmetic logic unit (ALU) built on ML Ga2O3 MOSFETs with the recently reported beyond-CMOS devices. Our results indicate that ML Ga2O3 can serve as a promising channel material in the post-silicon era.