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A vision-based motion capture and recognition framework for behavior-based safety management

Title
A vision-based motion capture and recognition framework for behavior-based safety management
Author
한상욱
Keywords
Safety; Behavior-based safety analysis; Vision-based tracking; Motion capture; Motion recognition
Issue Date
2013-11
Publisher
Elsevier Science B.V
Citation
Automation In Construction, 2013, 35, P.131-141
Abstract
In construction, about 80%-90% of accidents are associated with workers' unsafe acts. Nevertheless, the measurement of workers' behavior has not been actively applied in practice, due to the difficulties in observing workers on jobsites. In an effort to provide a robust and automated means for worker observation, this paper proposes a framework of vision-based unsafe action detection for behavior monitoring. The framework consists of (1) the identification of critical unsafe behavior, (2) the collection of relevant motion templates and site videos, (3) the 3D skeleton extraction from the videos, and (4) the detection of unsafe actions using the motion templates and skeleton models. For a proof of concept, experimental studies are undertaken to detect unsafe actions during ladder climbing (i.e., reaching far to a side) in motion datasets extracted from videos. The result indicates that the proposed framework can potentially perform well at detecting predefined unsafe actions in videos. (C) 2013 Elsevier B.V. All rights reserved.
URI
http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=50&SID=F22ft5AY9lV5zE8olqB&page=1&doc=1http://hdl.handle.net/20.500.11754/51309
ISSN
0926-5805; 1872-7891
DOI
10.1016/j.autcon.2013.05.001
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > CIVIL AND ENVIRONMENTAL ENGINEERING(건설환경공학과) > Articles
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