The invention discloses an experimental method based on crowd disaster video data and virtual scene reconstruction, and the method comprises the steps: carrying out the frame-by-frame analysis of an obtained
disaster monitoring video, dividing the
disaster monitoring video into a close-shot region and a long-shot region, and extracting the two-dimensional coordinate positions capable of recognizing individual pedestrians through employing a target detection technology, the
crowd density estimation technology is adopted to obtain overall
density distribution data, and a particle image
velocity measurement tool is utilized to extract the velocity and direction of pixel motion frame by frame. Establishing a three-dimensional virtual scene model corresponding to a real accident scene, mapping the processed crowd position and motion information into three-dimensional data matched with a virtual scene through a
coordinate projection tool, endowing the three-dimensional data with a unique identity
label, and carrying out cross-frame association and
trajectory optimization processing according to a
time sequence and a spatial proximity relationship; and generating a three-dimensional
pedestrian continuous track file for
virtual reality simulation, driving the dynamic position and posture change of a virtual
pedestrian entity, and realizing credible
reproduction of a crowd disaster situation and human in-loop experiment evaluation.