Abstract:This study explores the application of computer vision measurement technology in the realm of digitalized and intelligent engineering supervision. The research begins by outlining the foundational principles of computer vision and the concept of digitalized engineering supervision, followed by an analysis of the current state of computer vision applications within the engineering sector. The study identifies gaps in existing research and positions its objectives accordingly. A detailed design and implementation of a computer vision measurement system are presented, emphasizing system design principles, hardware and software architectures, and the integration of key technologies and algorithms. The application framework of computer vision technology in digitalized supervision is then discussed, covering scenarios such as quality control, progress and safety management, resource optimization, and decision support. A case study is conducted to validate the practical implementation of computer vision technology in engineering supervision, providing insights into its effectiveness and challenges. The conclusion summarizes the findings, discusses the theoretical and practical implications of the research, and suggests directions for future studies.