Automated object identification using optical video cameras on construction sites

Chi, Seokho & Caldas, Carlos (2011) Automated object identification using optical video cameras on construction sites. Computer-Aided Civil and Infrastructure Engineering, 26(5), pp. 368-380.

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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.

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40 citations in Web of Science®

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ID Code: 41851
Item Type: Journal Article
Refereed: Yes
Additional Information: Special Issue on Advances in Construction Automation
Keywords: interpretation of recorded images, automated object identification, mobile heavy equipment, construction sites
DOI: 10.1111/j.1467-8667.2010.00690.x
ISSN: 1093-9687
Subjects: Australian and New Zealand Standard Research Classification > BUILT ENVIRONMENT AND DESIGN (120000) > BUILDING (120200) > Building Construction Management and Project Planning (120201)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Urban Development
Copyright Owner: Copyright 2011 Wiley-Blackwell Publishing, Inc.
Deposited On: 31 May 2011 21:29
Last Modified: 31 May 2011 21:29

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