Point Cloud Geometry Syntax Constraints for Accurate Slice Decoding
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Solution Overview
Problem
Existing high-level syntax designs for geometry-based point cloud compression suffer from issues such as dimensions of a region box exceeding slice dimensions, lack of restrictions on slice IDs, inappropriate application of delta quantization parameters, and unrestricted value ranges for parameter set IDs, leading to increased signaling overhead, processing power waste, and decoding errors.
Innovation Solution
Implementing techniques that constrain region box dimensions within slice bounds, restrict slice IDs to ensure unique content, allow multiple regions for delta quantization, and enforce value range restrictions on parameter set IDs to reduce signaling overhead and prevent decoding errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If region box dimensions are allowed to exceed slice dimensions, then more flexible region definition is achieved, but signaling overhead increases and processing power is wasted
Solution Approach 1:
The patent applies parameter changes by modifying the dimension constraints of the region box to ensure it does not exceed the slice bounding box dimensions. This constraint is implemented through syntax elements in the bitstream that define the region box width, height, and depth, which are now bounded by the slice dimensions. This resolves the contradiction by maintaining flexibility within defined boundaries while preventing unnecessary signaling overhead.
2Adaptability or versatility
If slice IDs are unrestricted, then more slices can be created, but decoding errors increase due to duplicate IDs
Solution Approach 1:
The patent implements parameter changes by enforcing uniqueness constraints on slice IDs through syntax elements in the bitstream. The decoder is configured to check for duplicate slice IDs and handle them appropriately, ensuring that each slice within a tile has a unique identifier. This maintains slice creation flexibility while preventing decoding errors caused by duplicate IDs.
3Productivity
If delta quantization parameters are applied without region restrictions, then more regions can be optimized, but processing power is wasted on empty regions
Solution Approach 1:
The patent applies local quality by restricting delta quantization parameter application to only those regions that contain points. The syntax elements define region boxes with specific width, height, and depth parameters that are checked against the slice bounding box. If a region box does not contain any points (i.e., it is outside the valid point cloud region), the delta quantization parameter is not applied. This optimizes processing by focusing computational resources only on regions that actually contain data.
4Adaptability or versatility
If parameter set ID value ranges are unrestricted, then more parameter sets can be referenced, but device complexity increases
Solution Approach 1:
The patent implements parameter changes by defining specific value range constraints for parameter set IDs through syntax elements in the bitstream. The encoder signals the maximum value for parameter set IDs, and the decoder is configured to enforce this constraint. This maintains the ability to reference multiple parameter sets while reducing device complexity by establishing clear boundaries for valid ID values.
Data Source
AI summary
An example device for decoding point cloud data includes memory configured to store the point cloud data and one or more processors implemented in circuitry and coupled to the memory. The one or more processors are configured to determine dimensions of a region box and determine dimensions of a slice bounding box. The one or more processors are also configured to decode a slice of the point cloud data associated with the slice bounding box. The dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.