Multi-camera systems have been widely adopted due to their high resistance to interference and balanced spatial precision. However, existing research lacks a systematic framework for evaluating critical configuration parameters, such as the number of cameras, their angular distribution, and baseline settings. To address this gap, this Letter proposes a measurement precision model based on error analysis theory, enabling efficient estimation of system performance to guide both hardware selection and spatial arrangement. Experimental results validate that the proposed model provides a fast, reliable, and practical reference for the design and optimization of multi-camera configurations.

Fringe projection profilometry (FPP) is one of the most prominent non-interferometric high-precision 3D shape measurement techniques for measuring dimensions ranging from 1 mm to 1 m, with increasing applications in precision engineering. Thorough theoretical understanding of the precision of the prevailing FPP methods is critical when facing the challenges of higher precision demands. In this paper, through theoretical analysis of three reconstruction methods based on the projection of vertical fringes (Ver3), horizontal fringes (Hor3) and optimal-angle fringes (OptE3), we establish a general unified precision model, from which a general Pythagoras relationship is discovered, clarifying the optimal precision of OptE3. We then simplify the model to reveal the role of a system’s geometry for easier configuration. First, a special yet not restrictive case where the direction of the optical axis of the projector is perpendicular to the baseline of the FPP is considered, resulting in an intermediate unified precision model. We show that the effective baselines of the three methods obey a special Pythagoras relationship. Second, the angle between the optical axes of the camera and the projector is interestingly delineated from the projector’s extrinsic parameters, leading to our final and simplified unified precision model. This simplified model is geometrically tangible and thus eases the determination of the positions and orientations of the projector and camera in system configuration, given a precision budget, for which, an FPP-Planner software tool is prototyped. Going beyond, we theoretically equivalate FPP with stereo vision and laser triangulation regarding precision. Our findings are experimentally validated. These theoretical models are believed to potentially enhance or even change the way of FPP design and performance evaluation.

A novel method of geometric dimension assisted absolute phase recovery in 3D shape measurement is presented. This method mainly includes two steps: (a) using the window Fourier filter-quality guided phase unwrapping algorithm to obtain the relative phase distribution of the tested object; (b) using the geometric dimension of the object as a clue to convert the relative phase distribution to the absolute phase distribution. This method is convenient, and only three fringe image acquisitions are needed to recover the absolute phase. In addition, there is no limit to the depth range of the tested object. The correctness of this method is verified by several experiments.

In this paper a new method to extend the measurement depth limited by geometric constraints for objects with large depth variances is presented. This method mainly includes the following steps: (1) using the watershed image segmentation algorithm to extract the correct part of the discontinuous absolute phase distribution obtained by geometric constraints, and making a binary mask of the correspondent region; (2) using the window Fourier filter-quality guided phase unwrapping algorithm to obtain the relative phase distribution of the tested object; (3) using the binary mask to get the difference between the relative and the absolute phases; (4) converting the relative phase distribution to absolute phase distribution by referring to their phase difference in the mask region. The experimental results prove the effectiveness and correctness of the proposed method.

Cyborg insects offer a biologically powered solution for locomotion control, but conventional methods typically rely on invasive electrical stimulation. Here, we introduce a noninvasive, phototaxis-based strategy to steer walking Endebius florensis beetles using light-emitting diode (LED) stimuli. Electroretinogram recordings revealed spectral sensitivity to blue, green, and yellow light, with reduced response to red. Behavioral assays demonstrated robust positive phototaxis to blue light and negative phototaxis to yellow. Using these findings, we built a wireless microcontroller-based backpack emitting directional blue light to induce steering. The beetles reliably turned toward the activated light, achieving angular deflections over 60° within seconds. This approach enables repeatable, trauma-free insect control and establishes a new paradigm for biohybrid locomotion systems.

This Letter reveals two special geometric points and a geometric projection identity (GPI) within an FPP system, thereby providing new 3D reconstruction equations for four common methods (Ver3, Hor3, OptE3, and HorVer4). We prove that the GPI-based and the traditional reconstruction frameworks are equivalent, but the former enables much faster point cloud computation and effective analysis of precision for metrology.