Point Cloud Attribute Hierarchization Using Centroid Reference Points
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Solution Overview
Problem
Existing methods for encoding 3D data, such as point clouds, suffer from decreased encoding efficiency due to suboptimal selection of reference points in hierarchization processes.
Innovation Solution
The proposed solution involves setting the reference point based on the centroid of points or distribution mode in the point cloud, alternately selecting points closer to and farther from the bounding box center, and encoding information about the reference point setting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the reference point is selected using Morton order (first point and last point alternately), then the hierarchization process can be implemented with simple rules, but the encoding efficiency decreases
Solution Approach 1:
The patent changes the parameter for reference point selection from Morton order (first/last point alternation) to centroid-based selection. By calculating the centroid of all points and selecting the point closest to the centroid as the reference point, the system achieves better prediction accuracy and encoding efficiency while maintaining the simplicity of the hierarchization process.
2Productivity
If the reference point is selected based on centroid of points, then the prediction accuracy and encoding efficiency are improved, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary calculation of the centroid for the entire point cloud before the hierarchization process begins. By pre-computing the centroid position, the system avoids the need to recalculate centroids at each hierarchy level, thereby reducing the overall computational complexity while still benefiting from centroid-based reference point selection.
Solution Approach 2:
Instead of calculating the actual centroid position for each hierarchy level, the patent uses the pre-computed centroid as a reference and selects the closest point to this fixed reference position. This approach copies the centroid concept without requiring repeated complex calculations, simplifying the process while maintaining effectiveness.
Data Source
AI summary
There is provided an information processing device and method capable of suppressing a reduction in encoding efficiency. When performing, for attribute information of each point of a point cloud that represents an object having a three-dimensional shape as a set of points, hierarchization of the attribute information by recursively repeating classification of a prediction point for deriving a difference value between the attribute information and a predicted value of the attribute information and a reference point used for deriving the predicted value with respect to the reference point, the reference point is set on the basis of a centroid of points. The present disclosure can be applied to, for example, an information processing device, an image processing device, an encoding device, a decoding device, an electronic device, an information processing method, a program, and the like.