Computer Vision Automated Productivity Measurement

The objective of this research is to investigate the performance of a new method that can automatically detect the task cycles of construction activities, measure their duration, and compile reliable statistics based on 100% of the observed data. This can be achieved by applying primarily computer vision and machine learning techniques to process jobsites’ video data. The extracted construction entities’ trajectories will then be used for the detection of possible repeated work cycles by implementing statistical pattern recognition models. An overview of the project can be found in the attached figures.

Leading researcher: Eirini Konstantinou.