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Automated Object Identification Using Optical Video Cameras on Construction Sites

2010; Wiley; Volume: 26; Issue: 5 Linguagem: Inglês

10.1111/j.1467-8667.2010.00690.x

1467-8667

Seokho Chi, Carlos Caldas,

Video Surveillance and Tracking Methods

Computer-Aided Civil and Infrastructure EngineeringVolume 26, Issue 5 p. 368-380 Automated Object Identification Using Optical Video Cameras on Construction Sites Seokho Chi, Seokho Chi School of Urban Development, Queensland University of Technology, QLD 4001, AustraliaSearch for more papers by this authorCarlos H. Caldas, Corresponding Author Carlos H. Caldas Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, TX 78712, USA To whom correspondence should be addressed. E-mails: caldas@mail.utexas.edu; toalexdad@gmail.com.Search for more papers by this author Seokho Chi, Seokho Chi School of Urban Development, Queensland University of Technology, QLD 4001, AustraliaSearch for more papers by this authorCarlos H. Caldas, Corresponding Author Carlos H. Caldas Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, TX 78712, USA To whom correspondence should be addressed. E-mails: caldas@mail.utexas.edu; toalexdad@gmail.com.Search for more papers by this author First published: 15 November 2010 https://doi.org/10.1111/j.1467-8667.2010.00690.xCitations: 134Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Abstract: Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity. Citing Literature Volume26, Issue5July 2011Pages 368-380 RelatedInformation