Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75999
Title: Automatic key frame extraction in continuous videos from construction monitoring by using color, texture, and gradient features
Authors: Chen, L 
Wang, YH 
Keywords: Construction video archiving
Scene transition detection
Image feature selection
Key frame extraction
Issue Date: 2017
Publisher: Elsevier
Source: Automation in construction, 2017, v. 81, p. 355-368 How to cite?
Journal: Automation in construction 
Abstract: 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.
URI: http://hdl.handle.net/10397/75999
ISSN: 0926-5805
EISSN: 1872-7891
DOI: 10.1016/j.autcon.2017.04.004
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