Point Cloud Labeling via Camera Image Projection
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Solution Overview
Problem
Manual labeling of point cloud data is slow and prone to errors due to the lack of distinct object characteristics, especially when dealing with large volumes of data and similar features.
Innovation Solution
A method and apparatus that project point cloud data onto a camera image, allowing users to label objects by adding marks in the projected area, facilitating correct and efficient labeling through the combination of three-dimensional and two-dimensional data recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual labeling of point cloud data is used, then labeling can be performed without additional equipment, but labeling speed is slow and error rate is high
Solution Approach 1:
The patent introduces a camera image as an intermediary medium between the point cloud data and the labeler. The camera image provides a clear 2D visual reference that mediates the labeling process, allowing labelers to accurately identify objects in the point cloud by cross-referencing with the corresponding 2D image, thereby improving both speed and accuracy
Solution Approach 2:
The patent transforms the 3D point cloud data into a 2D projected area on the camera image. This dimensionality change allows labelers to leverage their familiarity with 2D image recognition while maintaining correspondence with the 3D point cloud, improving labeling efficiency and accuracy simultaneously
2Ease of operation
If manual labeling of point cloud data is used, then no additional processing equipment is needed, but objects with similar features are easily labeled incorrectly
Solution Approach 1:
The camera image serves as an intermediary that enhances object distinguishability. By projecting the 3D point cloud area onto the 2D camera image, objects with similar features become more distinguishable through the additional visual context provided by the 2D representation
Solution Approach 2:
The transformation from 3D point cloud to 2D projected area provides an alternative viewing dimension that enhances feature distinguishability. Objects that appear similar in 3D space can be more easily differentiated when projected onto the 2D camera image plane
Data Source
AI summary
The present application discloses a method and an apparatus for processing point cloud data. The method in an embodiment comprises: presenting a to-be-labeled point cloud frame and a camera image formed by photographing an identical scene at an identical moment as the point cloud frame; determining, in response to an operation of selecting an object in the point cloud frame by a user, an area encompassing the selected object in the point cloud frame; projecting the area from the point cloud frame to the camera image, to obtain a projected area in the camera image; and adding a mark in the projected area, for labeling, by the user, the selected object in the point cloud frame according to the mark indicating an object in the camera image. This implementation can assist labeling personnel in rapidly and correctly labeling an object in a point cloud frame.