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Automated Object Identification Using Optical Video Cameras on Construction Sites
Authors:Seokho Chi  Carlos H. Caldas
Affiliation:1. School of Urban Development, Queensland University of Technology, QLD 4001, Australia;2. Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, TX 78712, USA
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.
Keywords:
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