2023 Vol.6 Dec.N06

• Title: Research on abnormal behavior recognition in construction site based on feature fusion
• Name: Tianyuan Niu
• Company: Changchun Institute of Architecture, Changchun 130000, China
• Abstract:

  The current conventional abnormal behavior recognition method for construction construction site is mainly through the calibration of the on-site movement trajectory, and the abnormal behavior recognition is realized through the trajectory tracking, which results in poor recognition accuracy due to the lack of fusion processing of abnormal behavior features. In this regard, the abnormal behavior recognition technology of construction site based on feature fusion is proposed. Firstly, combining the channel attention mechanism model, the time domain features of the image of the building construction site are extracted, and the abnormal behavior features are fused to achieve the calibration of the abnormal behavior region, and finally the behavior detection network structure is constructed. In the experiments, the proposed method is verified for abnormal behavior recognition accuracy. Analysis of the experimental results shows that when the proposed method is used to identify abnormal behavior at the construction site, the accuracy of the algorithm is high, and it has a more ideal recognition effect.

  
  

• Keyword: feature fusion; construction site; abnormal behavior; recognition methods;
• DOI: 10.12250/jpciams2023090806
• Citation form: Tianyuan Niu.Research on abnormal behavior recognition in construction site based on feature fusion [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.26-31

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