Dynamic obstacle point cloud annotating method and apparatus, device and readable medium

A computer device, wherein the device comprises:

• one or more processors;
• a storage for storing one or more programs;
• a laser radar used to scan point cloud data under a static scenario around a target collecting point or under a dynamic scenario after a dynamic obstacle moves;
• the one or more programs, when executed by said one or more processors, enable said one or more processors to implement a dynamic obstacle point cloud annotating method, wherein the method comprises:
• collecting first point cloud data under a static scenario around a target collecting point;
• building a static background mesh model under the static scenario around the target collecting point according to the first point cloud data;
• collecting a second point cloud data of a target frame under a dynamic scenario after a dynamic obstacle moves around the target collecting point;
• annotating the point cloud of dynamic obstacle in the second point cloud data corresponding to the target frame, according to the static background mesh model,
• wherein the building a static background mesh model under the static scenario around the target collecting point according to the first point cloud data specifically comprises:
• performing mesh processing for the first point cloud data in a 3-dimensinal space to obtain a 3-dimensional mesh model;
• setting a background attribute for the corresponding mesh according to whether or not each mesh in the 3-dimensional mesh model includes valid points in the first point cloud data, to obtain the static background mesh model under the static scenario around the target collecting point,
• wherein the step of, according to whether each mesh in the 3-dimensional mesh model includes valid points in the first point cloud data, setting a background attribute for the corresponding mesh specifically comprises:
• judging whether meshes in the 3-dimensional mesh model include valid points in the first point cloud data, and if yes, setting the background attribute of the corresponding mesh as 1;
• otherwise, setting the background attribute of the corresponding mesh as 0,
• wherein the annotating the point cloud of dynamic obstacle in the second point cloud data corresponding to the target frame, according to the static background mesh model specifically comprises:
• projecting each target point of the second point cloud data into the static background mesh model;
• obtaining the background attribute of the mesh in the static background mesh model into which each target point is projected;
• according to the background attribute of the mesh in the static background mesh model into which each target point is projected, recognizing whether the corresponding target point belongs to a point of the dynamic obstacle;
• performing clustering processing for all points belonging to dynamic obstacles in the second point cloud data, to obtain the corresponding point cloud of dynamic obstacle.

A non-transitory computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements a dynamic obstacle point cloud annotating method, wherein the method comprises:

• collecting first point cloud data under a static scenario around a target collecting point;
• building a static background mesh model under the static scenario around the target collecting point according to the first point cloud data;
• collecting a second point cloud data of a target frame under a dynamic scenario after a dynamic obstacle moves around the target collecting point;
• annotating the point cloud of dynamic obstacle in the second point cloud data corresponding to the target frame, according to the static background mesh model,
• wherein the building a static background mesh model under the static scenario around the target collecting point according to the first point cloud data specifically comprises:
• performing mesh processing for the first point cloud data in a 3-dimensinal space to obtain a 3-dimensional mesh model;
• setting a background attribute for the corresponding mesh according to whether or not each mesh in the 3-dimensional mesh model includes valid points in the first point cloud data, to obtain the static background mesh model under the static scenario around the target collecting point,
• wherein the step of, according to whether each mesh in the 3-dimensional mesh model includes valid points in the first point cloud data, setting a background attribute for the corresponding mesh specifically comprises:
• judging whether meshes in the 3-dimensional mesh model include valid points in the first point cloud data, and if yes, setting the background attribute of the corresponding mesh as 1;
• otherwise, setting the background attribute of the corresponding mesh as 0,
• wherein the annotating the point cloud of dynamic obstacle in the second point cloud data corresponding to the target frame, according to the static background mesh model specifically comprises:
• projecting each target point of the second point cloud data into the static background mesh model;
• obtaining the background attribute of the mesh in the static background mesh model into which each target point is projected;
• according to the background attribute of the mesh in the static background mesh model into which each target point is projected, recognizing whether the corresponding target point belongs to a point of the dynamic obstacle;
• performing clustering processing for all points belonging to dynamic obstacles in the second point cloud data, to obtain the corresponding point cloud of dynamic obstacle.