3D posture estimation from 2D posture data for construction workers

Y. Yu, H. Li, X. Yang

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review

2 Citations (Scopus)

Abstract

Construction workers’ behaviour is important for safety, health and productivity management. Workers’ 3D postures are the data foundation of their behaviours. This paper established a preliminary 3D posture dataset of construction tasks and provided a 3D posture estimation method based on 2D joint locations. The results showed that the method could estimate 3D postures accurately and timely. The mean joint error and estimation time of each frame were 1.10 cm and 0.12 ms respectively. This method makes it possible to estimate construction workers’ 3D postures from construction site images and contributes to a data-based construction workers’ behaviour management.

Original languageEnglish
Pages26-34
Number of pages9
Publication statusPublished - 2019
Event36th International Symposium on Automation and Robotics in Construction, ISARC 2019 - Banff, Canada
Duration: 21 May 201924 May 2019

Conference

Conference36th International Symposium on Automation and Robotics in Construction, ISARC 2019
Country/TerritoryCanada
CityBanff
Period21/05/1924/05/19

Keywords

  • Behavior management
  • Construction worker
  • Posture estimation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Building and Construction
  • Human-Computer Interaction

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