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A worker posture coding scheme to link automatic and manual coding

delete2021-05-01
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PRE
AI
H
Hainan Chen
X
Xiaowei Luo *
Z
Zhenhua Zhu
DOI:10.1016/j.autcon.2021.103630delete
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Abstract

Abstract

En 中文
Real-time and automatic monitoring of worker behaviors and activities have great potential to improve construction job site operation. Traditional behavior monitoring of construction workers relies on human interpretation to determine workers? semantic conditions (e.g., tasks performing, safety status). Although advanced sensing technologies provide more accurate quantitative data on worker behavior, how to effectively link the data to a worker?s semantic condition in a form that is understandable for humans remains a challenge. This paper proposed a novel posture coding scheme based on the worker?s body part relative position (BPRP) information. The proposed coding scheme compresses the quantitative 3D skeleton data into qualitative posture descriptions but keeps the body part relative space information. Afterward, an indoor motion test is conducted to validate the reliability of the proposed BPBR coding scheme. The test results showed that by employing the BPRP coding scheme, the manual and automatic posture coding could achieve consistent results. Therefore, the manual posture coding results can be transformed into human skeleton figures and then further processed by the quantitative algorithms. Correspondingly, the computer-captured human skeleton data can be easily connected to the manual observation results by interpreting the BPRB codes
Keywords:
Human body posture
Coding consistency
Manual and automatic body posture coding& nbsp
connection
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Journal

Automation in Construction cover
Automation in Construction
IF:
11.5
Papers:
6.3K
Citations:
4.2W

Organization

S
Sun Yat Sen University
Scholars:
9.9W
Papers: 7.2W
Citations: 95
C
City University of Hong Kong
Scholars:
2.3W
Papers: 3.0W
Citations: 6.1W
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