Automatic key frame extraction in continuous videos from construction monitoring by using color, texture, and gradient features

- Color features less sensitive to illuminance change in construction are developed.
- Gradient features less affected by moving objects in construction are developed.
- Method of designing Gabor filter banks for construction videos is developed.
- An action based (AB) method for extracting key frames is developed.
- The developed image features outperform the existing popular ones.

On-site video recording systems are increasingly used for monitoring construction activities. The recorded videos contain rich and useful jobsite information that can be used for a variety of purposes. The large amount of video data generated by continuous monitoring, however, creates tremendous challenges on data storage and retrieval. Due to the relatively slow pace of construction activities, a significant portion of the recorded data is redundant. Therefore, archiving raw construction videos into a concise and structured set of key frames would facilitate data storage, retrieval and analysis. Three key issues in automatic key frame extraction from construction videos are studied, including the selection of proper video features, scene segmentation, and key frame extraction. New image features and methods are developed to address the three issues. A validation experiment indicates that the developed features and methods can effectively and efficiently extract representative key frames from the complex and dynamic construction videos. The developed techniques can be used to develop a construction video summary system that serves the purpose of effectively archiving construction jobsite videos.