Helmet Wearing Specification Action Recognition Dataset

In the current security industry, construction site safety management faces many challenges, such as the frequent occurrence of accidents due to the improper wearing of helmets by workers. Existing monitoring systems mostly rely on manual review, which is inefficient and prone to errors. This dataset aims to train models to automatically identify whether workers are wearing helmets and the correctness of their wearing, through high-quality video data, thereby improving the efficiency of safety management. Data collection is conducted using high-definition cameras in real construction site environments to ensure environmental diversity and data authenticity. To ensure data quality, a multi-round annotation and expert review mechanism is used for strict quality control. The data is stored in MP4 format and organized by work location and time for easy retrieval and analysis. The data annotation adopts a combination of automated tools and manual verification to ensure consistency and accuracy of annotations.