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Phase shifting profilometry (PSP) has been widely used in structured-light (SL) system for three-dimensional (3D) shape measurements, but the speed of PSP technique is limited by the increased phase-shifting patterns. This paper proposes an accurate and dynamic 3D shape measurement method by projecting only four patterns including three-step phase-shifting patterns and one speckle pattern. Three-step phase-shifting images are used to obtain the initial unwrapped phase map with phase ambiguity. Based on the principle of digital image correlation (DIC) and multi-view geometry, the absolute phase can be recovered reliably without requiring any embedded features or pre-defined information of the object. To improve the measurement accuracy, the projector coordinate is used as the measuring coordinate to establish a novel stereo structured-light system model. By solving a least square solution using the triple-view information, accurate 3D surface data can be reconstructed. The experimental results indicate that the proposed method can perform high-speed and accurate 3D shape measurements with an accuracy of 10.64 μm, which is superior to conventional methods and has certain instructive significance for 3D profilometry and measurement engineering.

Vision-based three-dimensional (3D) shape measurement techniques have been widely applied over the past decades in numerous applications due to their characteristics of high precision, high efficiency and non-contact. Recently, great advances in computing devices and artificial intelligence have facilitated the development of vision-based measurement technology. This paper mainly focuses on state-of-the-art vision-based methods that can perform 3D shape measurement with high precision and high resolution. Specifically, the basic principles and typical techniques of triangulation-based measurement methods as well as their advantages and limitations are elaborated, and the learning-based techniques used for 3D vision measurement are enumerated. Finally, the advances of, and the prospects for, further improvement of vision-based 3D shape measurement techniques are proposed.

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