Point Cloud Geometry Encoding With Radius-Scaled Azimuth Steps
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Solution Overview
Problem
Existing point cloud codecs, such as G-PCC, face challenges in achieving optimal compression performance, encoder simplicity, and low latency, particularly when dealing with sparse geometry data captured by a spinning sensor head, due to sub-optimal coding of the elementary azimuthal step in spherical coordinates.
Innovation Solution
The method involves dynamically scaling the elementary azimuthal step based on the decoded radius of points in a point cloud, using a scaled elementary azimuthal step that is greater than the elementary step when the radius is below a threshold, reducing the number of angular sectors and bits required for encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed elementary azimuthal step is used for encoding point cloud data, then the encoding process is simple, but the compression performance is poor for points at different distances from the sensor
Solution Approach 1:
The patent applies dynamics by making the elementary azimuthal step variable rather than fixed. The step size is dynamically adjusted based on the decoded radius of each point, allowing the encoding precision to adapt to the distance from the sensor. This resolves the contradiction by maintaining simplicity through an automated adaptive mechanism while improving compression performance through distance-aware precision adjustment.
Solution Approach 2:
The patent changes the parameter of elementary azimuthal step from a constant value to a variable value that depends on the radius parameter. By modifying this encoding parameter based on spatial distance, the system achieves better compression performance without significantly increasing encoding complexity, as the change is driven by automated parameter adjustment rather than complex processing.
2Measurement precision
If high precision encoding is used for all points, then the accuracy is maintained, but the number of bits required increases significantly
Solution Approach 1:
The patent applies local quality by differentiating the encoding precision based on the local position of each point relative to the sensor. Points closer to the sensor use a smaller azimuthal step (higher precision), while points farther away use a larger step (lower precision). This local adaptation maintains accuracy where needed while reducing the total number of bits required for encoding the entire point cloud.
Solution Approach 2:
The patent changes the encoding parameter (azimuthal step size) based on the radius parameter of each point. This parameter change allows the system to adjust precision locally, maintaining measurement accuracy for nearby points while using fewer bits for distant points, thus resolving the contradiction between precision and data quantity.
3Ease of manufacture
If traditional point cloud compression is used, then the encoding is straightforward, but the latency is high for real-time applications
Solution Approach 1:
The patent applies preliminary action by performing the radius-based step size determination before the actual azimuthal angle encoding. This preliminary calculation of the appropriate step size based on decoded radius allows for more efficient subsequent encoding operations, reducing overall latency while maintaining process simplicity through a structured two-stage approach.
Data Source
AI summary
A method of encoding a point cloud into a bitstream, each point of the point cloud being associated with spherical coordinates representing an azimuthal angle and a radius, includes: obtaining a scaled elementary azimuthal step associated with a point of the point cloud, the scaled elementary azimuthal step being equal to first data greater than an elementary azimuthal step in response to second data being strictly lower than a threshold, and being equal to the elementary azimuthal step otherwise; encoding, in the bitstream, a number of scaled elementary azimuthal steps obtained from an azimuthal angle of the point, a prediction of the azimuthal angle and the scaled elementary azimuthal step; and encoding, in the bitstream, an residual azimuthal angle of the point between the azimuthal angle of the point and a predicted azimuthal angle derived from the number of scaled elementary azimuthal steps and the scaled elementary azimuthal step.