3D Point Cloud Encoding Using N-ary Tree Bit Sequences
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Solution Overview
Problem
Current methods for encoding three-dimensional data are inefficient, particularly in representing and transmitting large volumes of point cloud data, which hinders effective use in applications like autonomous vehicles and map information systems.
Innovation Solution
A three-dimensional data encoding method that generates a bit sequence indicating the presence of points in child nodes of an N-ary tree structure, allowing for improved coding efficiency by selecting appropriate encoding modes based on the number of neighboring points, and decodes this information to restore the N-ary tree structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If point cloud data is stored and transmitted in its original form, then data completeness is maintained, but data transmission efficiency and storage requirements deteriorate due to the massive amount of data
Solution Approach 1:
The patent applies segmentation by dividing the point cloud data into an N-ary tree structure where the spatial space is recursively divided into child nodes. Each node contains only the information necessary to represent points within its spatial region, eliminating redundant data storage and improving transmission efficiency while maintaining complete spatial representation.
Solution Approach 2:
The patent transforms the traditional flat point cloud data representation into a hierarchical N-ary tree structure, adding a dimensional hierarchy to the data organization. This allows efficient compression by representing spatial relationships in multiple dimensions (parent-child node relationships) rather than storing all points independently.
2Measurement precision
If all child node information is encoded for every current node, then data accuracy is maintained, but coding complexity and data volume increase
Solution Approach 1:
The patent extracts only the essential information from child nodes - specifically, whether each child node contains points (occupancy information) and the position of the first point. This extraction approach maintains data accuracy for reconstruction while dramatically reducing coding complexity compared to encoding all child node attributes.
Solution Approach 2:
The patent implements partial encoding by only encoding information for child nodes that contain points, rather than encoding all possible child nodes. This partial action approach maintains necessary data accuracy while reducing overall coding complexity and data volume.
3Ease of manufacture
If traditional encoding methods are used for three-dimensional data, then implementation simplicity is maintained, but coding efficiency deteriorates
Solution Approach 1:
The patent changes the fundamental parameters of data representation by using an N-ary tree structure with occupancy codes and position information instead of traditional point cloud formats. This parameter change enables more efficient coding while maintaining relative implementation simplicity through systematic encoding rules that can be applied recursively.
Data Source
AI summary
A three-dimensional data encoding method includes: generating a bit sequence including N-bit information that is information of a current node included in an N-ary tree structure of three-dimensional points included in three-dimensional data and that indicates whether a three-dimensional point is present in each of child nodes belonging to the current node, where N is an integer greater than or equal to 2; generating (i) position information indicating a head position that is a position at which a predetermined code appears first in the bit sequence when the bit sequence is scanned in a predetermined scan order, and (ii) a remaining bit that is part of the bit sequence after the head position in the predetermined scan order; and encoding the position information and the remaining bit as information of the current node.