6DOF Volumetric Rendering with Clustered 3DOF+ View Encoding
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Solution Overview
Problem
Existing 3DOF+ volumetric video rendering experiences suffer from rendering artefacts due to zones with missing information, and increasing the number of viewpoints to reduce these artefacts leads to high data load, impacting storage and transport, and causing perceivable latency during seamless navigation.
Innovation Solution
The method involves clustering points in a 3D scene based on criteria such as depth, semantic classification, or motion, projecting these clusters into 2D images, and encoding them in separate or shared data streams, along with metadata, to facilitate efficient decoding and rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the number of viewpoints is increased to reduce rendering artefacts, then the quality of volumetric video is improved, but the data load increases significantly
Solution Approach 1:
The patent divides the 3D scene into multiple depth layers, with each layer containing points at similar depth ranges. This segmentation allows the system to process and transmit data for only the relevant depth layer at any given time, dramatically reducing the data load while maintaining rendering quality across multiple viewpoints.
Solution Approach 2:
The patent pre-calculates and stores occlusion relationships between different depth layers and viewpoints during the encoding phase. This preliminary action allows the decoder to quickly determine which data is already visible and which needs to be transmitted, avoiding redundant data transmission and reducing overall data load.
2Loss of information
If the number of viewpoints is increased to reduce rendering artefacts, then the completeness of scene information is improved, but the storage and transport requirements increase
Solution Approach 1:
By segmenting the scene into depth layers, the patent ensures that each layer's information is preserved and can be independently reconstructed. This allows complete scene information to be maintained across all layers while only transmitting the necessary portions for each viewpoint, reducing storage and transport requirements.
Solution Approach 2:
The patent applies different data transmission strategies to different depth layers based on their visibility requirements. Only the necessary depth layers for the current viewpoint are transmitted in full detail, while other layers use compressed or selective transmission, optimizing the balance between information completeness and data efficiency.
3Ease of operation
If data is transmitted for seamless navigation between viewpoints, then the user experience is improved, but the latency becomes perceivable
Solution Approach 1:
The patent pre-computes occlusion masks and visibility information during encoding, storing them for rapid retrieval during decoding. This preliminary preparation eliminates the need for real-time complex calculations during viewpoint transitions, significantly reducing latency while maintaining seamless navigation capability.
Solution Approach 2:
By organizing data into depth layers with pre-calculated occlusion relationships, the patent enables the decoder to quickly identify and retrieve only the necessary data for the current viewpoint. This segmented approach reduces data retrieval time and processing latency compared to handling all viewpoints' data uniformly.
4Quantity of substance
If 3DOF+ rendering is used to limit viewing space, then the data load is reduced, but rendering artefacts appear due to missing information
Solution Approach 1:
The patent segments the limited 3DOF+ viewing space into multiple depth layers, ensuring that each layer is properly reconstructed even within the constrained viewing volume. This segmentation allows efficient data representation that reduces load while preventing rendering artefacts through accurate depth-based reconstruction.
Solution Approach 2:
During encoding, the patent pre-processes the data to identify and mark occluded regions within the 3DOF+ viewing bounding box. This preliminary action allows the decoder to properly handle missing information by using depth layer reconstruction techniques, maintaining rendering quality without requiring data for the entire 360° space.
Data Source
AI summary
A volumetric content is encoded as a set of clusters by an encoder and transmitted to a decoder which retrieves the volumetric content. Clusters common to different viewpoints are obtained and mutualized. Clusters are projected onto 2D images and encoded as independent video streams. Reduction in visual artefacts and reduction of data for storage and streaming are achieved.


