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A Review of Computer Vision-Based Structural Deformation Monitoring in Field Environments.

Yizhou ZhuangWeimin ChenTao JinBin ChenHe ZhangWen Zhang
Published in: Sensors (Basel, Switzerland) (2022)
Computer vision-based structural deformation monitoring techniques were studied in a large number of applications in the field of structural health monitoring (SHM). Numerous laboratory tests and short-term field applications contributed to the formation of the basic framework of computer vision deformation monitoring systems towards developing long-term stable monitoring in field environments. The major contribution of this paper was to analyze the influence mechanism of the measuring accuracy of computer vision deformation monitoring systems from two perspectives, the physical impact, and target tracking algorithm impact, and provide the existing solutions. Physical impact included the hardware impact and the environmental impact, while the target tracking algorithm impact included image preprocessing, measurement efficiency and accuracy. The applicability and limitations of computer vision monitoring algorithms were summarized.
Keyphrases
  • deep learning
  • machine learning
  • mental health
  • healthcare
  • public health
  • risk assessment
  • health information
  • social media
  • neural network
  • health promotion