3D Point Cloud Encoding With Layer-Specific Quantization
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Solution Overview
Problem
Existing three-dimensional data encoding methods face challenges in efficiently encoding and decoding large volumes of point cloud data, necessitating improved compression techniques to facilitate transmission and accumulation.
Innovation Solution
A method and device for three-dimensional data encoding and decoding that utilize a hierarchical structure, where coefficient values are quantized using layer-specific quantization parameters, allowing for adaptive encoding and decoding with improved coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If viewpoint information is not included in the bit stream, then transmission bandwidth is saved, but the quality of three-dimensional image reproduction deteriorates due to visibility differences between left and right eyes
Solution Approach 1:
The encoder pre-calculates and encodes viewpoint information (virtual viewpoint positions) before actual image transmission. This allows the decoder to reconstruct accurate three-dimensional images by utilizing the pre-prepared viewpoint data, resolving the contradiction between bandwidth savings and image quality.
Solution Approach 2:
Viewpoint information acts as an intermediary element that bridges the gap between limited transmitted data and high-quality three-dimensional reconstruction. By encoding this intermediate information, the system enables accurate depth perception without transmitting complete multi-view image data.
2Manufacturing precision
If multiple cameras are used to capture three-dimensional information, then image quality and depth information are improved, but device complexity and cost increase
Solution Approach 1:
The imaging device is designed to perform multiple functions: capturing both two-dimensional images and three-dimensional information using the same hardware setup. By making the system multi-functional, it reduces the need for separate specialized equipment while maintaining three-dimensional reconstruction accuracy.
Solution Approach 2:
The system uses a single imaging device to capture images that will be processed and reconstructed into three-dimensional data. Instead of using multiple physical cameras, the method creates virtual copies of viewpoint information through computational processing, reducing hardware complexity while maintaining three-dimensional accuracy.
Data Source
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AI summary
A three-dimensional data encoding method includes: calculating coefficient values from pieces of attribute information of three-dimensional points included in point cloud data (S7091); quantizing the coefficient values individually to generate quantized values (S7092); and generating a bitstream including the quantized values (S7093). Each of the coefficient values belongs to any one of layers. In the quantizing (S7092), each of the coefficient values is quantized using a quantization parameter for a layer to which the coefficient value belongs among the layers, and the bitstream includes first information and pieces of second information, the first information indicating a reference quantization parameter, the pieces of second information being for calculating quantization parameters for the layers from the reference quantization parameter.