Tunnel scene recognition method and apparatus, and device and storage medium

A computer device, comprising a memory and a processor, the memory having a computer program stored therein, and the processor, when executing the computer program, causing the computer device to implement a tunnel scene recognition method including:

• acquiring point cloud data corresponding to a position of a motion path of a vehicle;
• segmenting the point cloud data into a plurality of point cloud subsets along different spatial positions on the motion path;
• for each point cloud subset, determining a ray cluster including a plurality of rays emitting from a ray origin on the vehicle to corresponding spatial points in the point cloud subset and a center point of the ray cluster based on positions of the spatial points in the ray cluster;
• determining closed-distribution characteristics of the spatial points in each point cloud subset based on first distances between the spatial points in the ray cluster and the ray origin and continuous-distribution characteristics of the spatial points in the point cloud subset based on a second distance between the center point of the ray cluster and the ray origin;
• and
• recognizing a motion sub-path in a tunnel scene in the motion path based on the closed-distribution characteristics and the continuous-distribution characteristics of respective spatial points in the plurality of point cloud subsets.

A non-transitory computer-readable storage medium, having a computer program stored therein, the computer program, when executed by a processor of a computer device, causing the computer device to implement a tunnel scene recognition method including:

• acquiring point cloud data corresponding to a position of a motion path of a vehicle;
• segmenting the point cloud data into a plurality of point cloud subsets along different spatial positions on the motion path;
• for each point cloud subset, determining a ray cluster including a plurality of rays emitting from a ray origin on the vehicle to corresponding spatial points in the point cloud subset and a center point of the ray cluster based on positions of the spatial points in the ray cluster;
• determining closed-distribution characteristics of the spatial points in each point cloud subset based on first distances between the spatial points in the ray cluster and the ray origin and continuous-distribution characteristics of the spatial points in the point cloud subset based on a second distance between the center point of the ray cluster and the ray origin;
• and
• recognizing a motion sub-path in a tunnel scene in the motion path based on the closed-distribution characteristics and the continuous-distribution characteristics of respective spatial points in the plurality of point cloud subsets.