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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).

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The strengths of both push and pull using both hands at handle heights of 75, 90, and 135 cm were measured for 11 female and 8 male participants. In addition, simulated push and pull tasks were performed on one of the three heights as in the strength measurements. In these tasks, the participants either pushed or pulled a swing suspended with one of the two loads (32.5 and 42.5 kg) until they could no longer do so. Then, the strength of push or pull was measured again. The participants also reported bodily discomfort on their body parts on a CR-10 rating scale. It was found that hands and leading leg had the highest CR-10 scores among the body parts and were the bottleneck body parts for the push and pull tasks, respectively. Models of maximum endurance time incorporating gender and handle height, in addition to force ratio, were developed. These models may be adopted in predicting the endurance time in job design concerning work/rest arrangement.

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