Method and device used for processing point cloud data

A point cloud data and point cloud technology, which is applied in the directions of measuring devices, image data processing, and re-radiation, can solve the problems of object labeling errors, slow labeling speed, and unobvious features of similar features, so as to eliminate Labeling errors, ensuring accuracy, and improving labeling efficiency
CN107871129AActive Publication Date: 2018-04-03BEIJING BAIDU NETCOM SCI & TECH CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING BAIDU NETCOM SCI & TECH CO LTD
Publication Date
2018-04-03

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Abstract

The invention discloses a method and device used for processing point cloud data. A concrete implementation method includes displaying a to-be-marked point cloud frame and a camera image formed by photographing one scene at the one moment by the point cloud frame; determining an area of an object in the point cloud frame in response to operation of selecting the object in the point cloud frame; projecting the area into the camera image from the point cloud frame and obtaining a projection area in the camera image; adding a mark in the projection area so as to enable a user to mark the selectedobject in the point cloud frame according to the object indicated by the mark in the camera image. By adopting the implementation method, aid can be provided to a marking worker to mark the object inthe point cloud frame quickly and accurately.
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Description

technical field

[0001] The present application relates to the field of computer technology, specifically to the field of data processing technology, and in particular to a method and device for processing point cloud data. Background technique

[0002] When training the recognition algorithm for point cloud data, it is necessary to use a large number of labeled point cloud data as training samples. Therefore, it is necessary to collect a large number of point cloud data of different scenes in advance and accurately label them to ensure the smooth progress of the optimization process. In the prior art, the collected point cloud data is usually marked manually.

[0003] However, the characteristics of objects in the point cloud are often not obvious, and they are also affected by the ground and other debris. Faced with a large amount of data that needs to be labeled, the labeling speed is slow when using manual labeling, and it is easy to have similar objects. The object of ...

Claims

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