Video-Based Point Cloud Compression Model to World Signaling
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Solution Overview
Problem
Current video-based point cloud compression technologies face inefficiencies in compressing dynamic 3D scenes due to poor temporal compression performance and limited 6DOF capabilities, as they struggle to adapt the origin and quantization volume of point cloud frames on a frame-to-frame basis and lack information about the pivot point for accurate transformation and scale preservation.
Innovation Solution
Introducing signaling information to adapt the model domain's origin and quantization volume relative to the world domain on a frame-to-frame basis, and providing parameters for pivot point, scale, rotation, and translation to ensure accurate conversion from the video-based point cloud compression domain to the world domain, enhancing encoding efficiency and fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video-based point cloud compression is used to compress dynamic 3D scenes, then compression is achieved, but temporal compression performance is poor and 6DOF capabilities are limited
Solution Approach 1:
The patent implements dynamic adaptation of the origin and quantization volume of point cloud frames on a frame-to-frame basis. This allows the compression system to dynamically adjust to temporal changes in the 3D scene, improving temporal compression performance by ensuring each frame is optimally quantized relative to the world domain rather than using a fixed quantization scheme.
Solution Approach 2:
The patent introduces signaling information that conveys parameters for adapting the model domain's origin and quantization volume relative to the world domain. By changing these parameters dynamically based on frame content and providing them through signaling, the system achieves better temporal compression while maintaining 6DOF capabilities.
2Device complexity
If fixed origin and quantization volume are used for point cloud frames, then device complexity is reduced, but adaptability to different frames and accurate transformation is lost
Solution Approach 1:
The patent performs preliminary adaptation of the origin and quantization volume for each point cloud frame before compression. By pre-calculating and signaling the transformation parameters (including pivot point information) that define the relationship between model domain and world domain, the system enables accurate transformation without adding complex runtime processing.
3Loss of information
If model domain to world domain conversion is performed without pivot point information, then signaling overhead is reduced, but accurate transformation and scale preservation are compromised
Solution Approach 1:
The patent applies local quality by providing pivot point information specifically where needed for accurate transformation. Rather than providing all possible transformation parameters unconditionally, the system selectively signals pivot point data based on whether transformation is required for that particular frame or object, optimizing the balance between signaling overhead and transformation accuracy.
Data Source
AI summary
Apparatuses, methods, and computer programs are disclosed to implement video-based cloud compression model to world signaling. An example apparatus includes at least one processor; and at least one non-transitory memory including computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform: provide first signaling information comprising information related to a world domain, wherein the world domain is a point cloud frame that is represented by a number of points in a first volumetric coordinate system; and provide second signaling information comprising information related to a conversion of a model domain to the world domain, wherein the model domain represents the point cloud frame by a number of points in a second volumetric coordinate system.