Point cloud densification method, terminal and storage medium
By creating a virtual point cloud and converting it into a virtual image for upsampling, the problem of sparse point clouds making it difficult to identify target objects is solved, and the density of point clouds and the labeling efficiency are improved.
CN119693728APending Publication Date: 2025-03-25HAOMO TECH CO LTD
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Patent Information
- Application Number
- CN202311232172.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-09-22
- Publication Date
- 2025-03-25
AI Technical Summary
Technical Problem
When labeling traditional point clouds, due to sparse point clouds, the target object is not easily recognized and the labeling efficiency is low.
Method used
By creating a virtual point cloud, it is converted into a virtual image for upsampling, improving the resolution of the virtual image, and then converting the upsampled virtual image into a dense point cloud.
Benefits of technology
The resolution of the point cloud is improved, making the target object clearer and easier to identify, thereby improving the efficiency of the point cloud when manually labeling.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention is suitable for the technical field of computers, and provides a point cloud densification method, a terminal and a storage medium, and the method comprises the steps: creating a virtual point cloud based on a target point cloud, the virtual point cloud comprises a plurality of virtual data points, and the vertical coordinates of the plurality of virtual data points are different, projections of the plurality of virtual data points on an XY plane of a coordinate system where the target point cloud is located are uniformly distributed; generating a virtual image corresponding to the virtual point cloud based on the ordinates of the plurality of virtual data points in the coordinate system; performing up-sampling on the virtual image to obtain an up-sampled image; and based on the up-sampling image, determining a dense point cloud of the target point cloud. By means of the scheme, the defect that data points in the point cloud are sparse is overcome, the target object represented in the point cloud is clearer, the target object in the point cloud is easy to recognize, and then the efficiency of manual marking of the point cloud is improved.
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