Lidar Point Cloud Labeling via 2D Projection
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Solution Overview
Problem
Manual labeling of 3D LIDAR point clouds for object detection in autonomous vehicles is labor-intensive, inefficient, and prone to inaccuracies due to the complexity of visualizing 3D data on 2D interfaces, leading to low labeling efficiency and visual fatigue.
Innovation Solution
A system that processes 3D point cloud data by projecting it onto a 2D interface, allowing users to easily identify and label objects through a graphical user interface that superimposes 2D and 3D data, enabling efficient and accurate labeling by decomposing the task into 2D visualization steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual labeling of 3D LIDAR point clouds is performed using conventional tools, then labeling can be completed, but the process is labor-intensive and inefficient
Solution Approach 1:
The patent creates a 2D copy or projection of the 3D point cloud data that can be displayed and manipulated on a standard 2D display interface. This copied representation maintains the essential spatial relationships and object characteristics while being compatible with conventional display and interaction methods, thereby dramatically improving labeling efficiency without requiring specialized 3D display equipment
Solution Approach 2:
The patent transforms 3D point cloud data into a 2D projected representation, effectively reducing the dimensionality of the data for display purposes. This dimensionality change allows the complex 3D information to be visualized and interacted with on a 2D screen, making the labeling process more efficient and accessible while preserving the necessary spatial information for accurate object identification
2Ease of operation
If 3D point cloud data is visualized on a 2D interface, then the data can be displayed, but visualization complexity increases and accuracy decreases
Solution Approach 1:
The system creates a faithful 2D projection copy of the 3D point cloud that preserves critical spatial relationships and object characteristics. This copied representation maintains sufficient fidelity to the original 3D data to enable accurate labeling while being fully compatible with 2D display interfaces and conventional interaction methods
Solution Approach 2:
The patent replaces complex mechanical 3D visualization and manipulation systems with a computational approach that projects 3D data onto a 2D plane. This substitution eliminates the need for specialized 3D display hardware and complex manual manipulation of 3D interfaces, while maintaining labeling accuracy through intelligent projection algorithms that preserve essential spatial information
3Ease of operation
If existing labeling tools are used for 3D point clouds, then labeling can be performed, but the tools are not user friendly and cause visual fatigue
Solution Approach 1:
The patent converts the 3D visualization problem into a 2D projection that can be displayed on standard screens using conventional display technologies. This dimensionality change allows the use of familiar 2D interface paradigms and display characteristics, making the tool more user-friendly and reducing visual fatigue associated with complex 3D interface manipulation
Solution Approach 2:
The patent creates a labeling system that works with standard 2D display interfaces while handling 3D point cloud data. This universal approach allows the tool to function effectively on conventional displays without requiring specialized hardware, thereby improving ease of operation and reducing visual fatigue by using familiar display characteristics and interaction patterns
Data Source
AI summary
Systems and methods for processing point cloud data are disclosed. The methods include receiving a 3D image including point cloud data, displaying a 2D image of the 3D image, and generating a 2D bounding box that envelops an object of interest in the 2D image. The methods further include generating a projected image frame comprising a projected plurality of points by projecting a plurality of points in a first direction. The methods may then include displaying an image frame that includes the 2D image and the 2D bounding box superimposed by the projected image frame, receiving a user input that includes an identification of a set of points in the projected plurality of points that correspond to the object of interest, identifying a label for the object of interest, and storing the set of points that correspond to the object of interest in association with the label.