3D Point Cloud Refinement Using Quantizer Shifts
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Solution Overview
Problem
Existing technologies face challenges in efficiently compressing and distributing dynamic 3D point clouds while maintaining high quality and low bit-rate consumption.
Innovation Solution
A method and apparatus for point cloud decoding and encoding that involve obtaining data from multiple point clouds, applying quantizer shifts, and refining point cloud data to maximize conditional probabilities and prior probabilities, thereby enhancing precision and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional latticed-based algorithms are used for point cloud processing, then the processing is straightforward for regular data, but they cannot handle unorganized 3D point clouds that are sparsely and irregularly scattered
Solution Approach 1:
The patent transforms the point cloud data from irregular 3D space into a structured representation by changing parameters including spatial coordinates, intensity values, and temporal characteristics. This allows applying traditional signal processing techniques to unorganized point clouds while maintaining their inherent properties
Solution Approach 2:
The patent segments the point cloud data into multiple components including spatial information, intensity attributes, and temporal frames. This segmentation enables independent processing of each component using appropriate algorithms, making unorganized point clouds manageable while preserving data integrity
2Measurement precision
If multiple measurements from multiple observations are used to enhance precision, then the measurement precision improves, but the device complexity and processing requirements increase
Solution Approach 1:
The patent merges multiple measurements from different observations by aligning point clouds from multiple frames and sensors, combining their information to enhance precision. This merging process integrates spatial, temporal, and intensity data while managing complexity through efficient data structures and processing algorithms
Solution Approach 2:
The patent introduces intermediate representations and processing stages that mediate between raw multiple measurements and final enhanced output. These intermediaries include aligned point cloud frames, registered coordinate systems, and processed intensity maps, which simplify the overall processing complexity
3Productivity
If dynamic point clouds are compressed and distributed, then the productivity and distribution efficiency improve, but the quality of experience and precision may deteriorate
Solution Approach 1:
The patent performs preliminary actions during encoding including alignment, registration, and extraction of key features from point cloud data before compression. This preliminary processing preserves essential precision information while enabling efficient compression, ensuring quality is maintained during distribution
Solution Approach 2:
The patent applies different compression strategies to different parts of the point cloud data based on their importance. Critical spatial and intensity information is preserved with higher fidelity while less critical data undergoes more aggressive compression, maintaining overall quality while improving productivity
Data Source
AI summary
Systems and methods are described for refining first point cloud data using at least second point cloud data and one or more sets of quantizer shifts. An example point cloud decoding method includes obtaining data representing at least a first point cloud and a second point cloud; obtaining information identifying at least a first set of quantizer shifts associated with the first point cloud; and obtaining refined point cloud data based on at least the first point cloud, the first set of quantizer shifts, and the second point cloud. The obtaining of the refined point cloud data may include performing a subtraction based on at least the first set of quantizer shifts. Corresponding encoding systems and methods are also described.