Review of fringe projection profilometry: from geometric triangulation to computational 3D imaging

With the rapid advances in digital technologies and intelligent manufacturing, three-dimensional (3D) imaging based on fringe projection has laid the foundation for machine vision, industrial metrology, and interdisciplinary applications. This review provides a comprehensive overview of fringe projection profilometry (FPP), which is a widely adopted technology in the 3D imaging landscape. First, we outline the fundamental principles, implementation procedures, and historical developments of FPP. Next, we present the continuous advances in algorithms, hardware, and applications that collectively push FPP towards increasingly challenging measurement scenarios. Subsequently, we provide a dedicated discussion to explain the transformative roles of artificial intelligence (AI) and computational imaging (CI), delineating how their progress is initiating a shift from traditional geometric approaches towards computational 3D imaging. The current challenges and emerging trends in 3D imaging are further identified and discussed. Looking ahead, FPP is expected to evolve into a next-generation 3D imaging technique, achieving unprecedented accuracy, efficiency, and adaptability through the co-optimization of systems with algorithms and the convergence of AI and CI, thereby empowering more complex requirements across industrial, biomedical, and scientific domains.