The widespread adoption of surveillance cameras in work environments has enabled the direct and non-intrusive detection of productivity-related issues in the field of construction. In this research, a process monitoring and problem feedback framework is developed based on closed-circuit television footage and computer vision analysis to achieve real-time visual control of the work process and facilitate data-driven decision-making in off-site construction. To enhance the automation of productivity-related problem recognition, a novel video analysis algorithm is developed to process the inputted video footage and provide feedback with respect to nine productivity issues. The -score and Exponential Moving Average methods are employed to eliminate detection errors, and the spatial density analysis method is adopted to visually analyze spatial information. The observed performance of the proposed framework demonstrates that it can accurately acquire data from footage and provide process monitoring and problem feedback in real time.

中文翻译：

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基于视觉的实时过程监控和问题反馈，用于场外施工中以生产力为导向的分析

监控摄像头在工作环境中的广泛采用使得能够直接、非侵入性地检测建筑领域与生产力相关的问题。本研究基于闭路电视画面和计算机视觉分析，开发了过程监控和问题反馈框架，以实现工作过程的实时可视化控制，促进场外施工的数据驱动决策。为了增强生产力相关问题识别的自动化，开发了一种新颖的视频分析算法来处理输入的视频片段并提供有关九个生产力问题的反馈。采用-score和指数移动平均方法消除检测误差，采用空间密度分析方法对空间信息进行可视化分析。所提出的框架的观察到的性能表明它可以准确地从镜头中获取数据并实时提供过程监控和问题反馈。