ICON-Pose: Toward Egocentric Action Recognition for Intelligent Construction
Publication: Computing in Civil Engineering 2023
ABSTRACT
The working environment of construction workers is often hazardous and dynamic, leading not only to decline in worker productivity but also fatal accidents. Monitoring of workers’ behavior has thus gained increasing attention in the construction community for hazard monitoring, ergonomic analysis, and productivity estimation. Egocentric action recognition is robust and promising in identifying, localizing, and tracking workers’ actions. However, the insufficiency of publicly available datasets designated for egocentric construction workers’ action recognition hampers the training and evaluation of existing and newly developed deep-learning models. In this regard, this paper introduces ICON-Pose, the first open dataset built specifically for estimating construction workers’ poses via egocentric view. ICON-Pose offers hundreds of egocentric images and corresponding 2D workers’ body joints in 38 actions, categorized in 10 basic construction tasks, including “connect,” “cover,” “cut,” “dig,” “finish,” “place,” “position,” “spray,” “spread,” and “others.” ICON-Pose with the proposed pose estimation model demonstrates the ability in accurately depicting diverse construction workers’ poses as well as the robustness in describing unique construction poses. The proposed dataset is expected to invigorate and support artificial intelligence research in construction workers’ behavior tracking and has the potential of serving as a benchmark dataset for subsequent analysis.
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Published In
Computing in Civil Engineering 2023
Pages: 682 - 689
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Automation and robotics
- Business management
- Detection methods
- Disaster risk management
- Employment
- Engineering fundamentals
- Human and behavioral factors
- Labor
- Methodology (by type)
- Model accuracy
- Models (by type)
- Personnel management
- Practice and Profession
- Productivity
- Risk management
- Systems engineering
- Tracking
- Two-dimensional models
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