[논문]3D tracking of multiple onsite workers based on stereo vision

Lee, Yong-Ju; Park, Man-Woo

doi:10.1016/j.autcon.2018.11.017

3D tracking of multiple onsite workers based on stereo vision

Automation in construction, v.98, 2019년, pp.146 - 159

Lee, Yong-Ju (Corresponding author.) , Park, Man-Woo

Abstract ▼ AI-Helper

Abstract Varied sensing technologies have been delved in for positioning workers and equipment in construction sites. Vision-based technology has been received growing attentions by the virtue of its tag-free and inexpensive configuration. One of the core research works in this area was the use of stereo camera system for tracking 3D locations of construction resources. However, the previous work was limited to tracking of a single entity. To overcome the limitation, this paper presents a new framework for tracking multiple workers. The proposed framework supplements the previous work by embedding an additional step, entity matching, which finds corresponding matches of tracked workers across two camera views. Entity matching takes advantage of the epipolar geometry and workers' motion directions for finding correct pairs of a worker's projections on two image planes. This paper also presents an effective approach of camera calibration for positioning entities located a few tens of meters away from the cameras. The proposed framework is evaluated based on completeness, continuity, and localization accuracy of the generated trajectories. The evaluation results have shown its capability of retrieving 96% of actual movements, within localization errors of 0.821 m with 99.7% confidence. Highlights A vision-based framework to track multiple workers in 3D is proposed. Entity matching across stereo camera views is included in the framework. Camera calibration employs direct rectification and avoids using a checker board. The framework is evaluated based on the quality of generated trajectories. 96% of workers' movements are retrieved with the mean error of 0.293 m.

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3D tracking of multiple onsite workers based on stereo vision

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3D tracking of multiple onsite workers based on stereo vision

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