Abstracts – Browse Results
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Hallowell, M R, Hardison, D and Desvignes, M (2016) Information technology and safety: Integrating empirical safety risk data with building information modeling, sensing, and visualization technologies. Construction Innovation, 16(03), 323-47.
Holt, G D (2016) Opposing influences on construction plant and machinery health and safety innovations. Construction Innovation, 16(03), 390-414.
Karimi, H, Taylor, T R B, Goodrum, P M and Srinivasan, C (2016) Quantitative analysis of the impact of craft worker availability on construction project safety performance. Construction Innovation, 16(03), 307-22.
Lee, W and Migliaccio, G C (2016) Physiological cost of concrete construction activities. Construction Innovation, 16(03), 281-306.
Liu, M, Han, S and Lee, S (2016) Tracking-based 3D human skeleton extraction from stereo video camera toward an on-site safety and ergonomic analysis. Construction Innovation, 16(03), 348-67.
- Type: Journal Article
- Keywords: ergonomics,construction safety,stereo vision,computer vision,3d human skeleton extraction,motion tracking
- ISBN/ISSN:
- URL: https://doi.org/10.1108/CI-10-2015-0054
- Abstract:
Purpose As a means of data acquisition for the situation awareness, computer vision-based motion capture technologies have increased the potential to observe and assess manual activities for the prevention of accidents and injuries in construction. This study thus aims to present a computationally efficient and robust method of human motion data capture for the on-site motion sensing and analysis. Design/methodology/approach This study investigated a tracking approach to three-dimensional (3D) human skeleton extraction from stereo video streams. Instead of detecting body joints on each image, the proposed method tracks locations of the body joints over all the successive frames by learning from the initialized body posture. The corresponding body joints to the ones tracked are then identified and matched on the image sequences from the other lens and reconstructed in a 3D space through triangulation to build 3D skeleton models. For validation, a lab test is conducted to evaluate the accuracy and working ranges of the proposed method, respectively. Findings Results of the test reveal that the tracking approach produces accurate outcomes at a distance, with nearly real-time computational processing, and can be potentially used for site data collection. Thus, the proposed approach has a potential for various field analyses for construction workers’ safety and ergonomics. Originality/value Recently, motion capture technologies have rapidly been developed and studied in construction. However, existing sensing technologies are not yet readily applicable to construction environments. This study explores two smartphones as stereo cameras as a potentially suitable means of data collection in construction for the less operational constrains (e.g. no on-body sensor required, less sensitivity to sunlight, and flexible ranges of operations).
Siddula, M, Dai, F, Ye, Y and Fan, J (2016) Classifying construction site photos for roof detection: A machine-learning method towards automated measurement of safety performance on roof sites. Construction Innovation, 16(03), 368-89.
Teizer, J (2016) Right-time vs real-time pro-active construction safety and health system architecture. Construction Innovation, 16(03), 253-80.