3D Point Cloud Motion Estimation Using Auxiliary Data
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Solution Overview
Problem
Current methods for encoding and transmitting three-dimensional point cloud data are inefficient due to the large bandwidth requirements, as they typically involve encoding and transmitting entire frames of patches, which can be cumbersome and wasteful, especially when dealing with dynamic representations of point cloud media.
Innovation Solution
The proposed solution involves generating motion refinement data by comparing patches between frames and using a three-dimensional bounding box to project and segment the point cloud data, allowing for the transmission of motion vectors and auxiliary information to decode and reconstruct the point cloud data efficiently, thereby reducing bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entire frames of patches are encoded and transmitted, then accurate reconstruction of point cloud data is maintained, but bandwidth consumption increases significantly
Solution Approach 1:
The patent extracts only the essential motion information (motion vectors and auxiliary data) from the complete frame data, separating the critical motion refinement components from the redundant visual details. This allows transmission of only the necessary motion parameters rather than entire frames, significantly reducing bandwidth while preserving reconstruction accuracy through motion compensation.
Solution Approach 2:
The patent creates a compressed representation (motion refinement data) that copies the essential motion characteristics from the original frames. By encoding motion vectors that describe how patches move between frames, the system creates a compact copy containing only the critical transformation information, enabling accurate reconstruction without transmitting the full original frames.
2Loss of energy
If motion refinement data is transmitted instead of entire frames, then bandwidth consumption is reduced, but encoding complexity increases
Solution Approach 1:
The patent segments the point cloud data into multiple patches and divides the encoding process into manageable steps: first segmenting the 3D point cloud into 2D patches, then identifying motion vectors for each patch, and finally encoding only the motion refinement data. This segmentation approach reduces the complexity of handling large datasets by processing smaller units independently and systematically.
Solution Approach 2:
The patent performs preliminary actions by pre-segmenting the point cloud data into patches and pre-identifying motion vectors before the actual encoding transmission. This preparation work is done in advance to simplify the main encoding process, allowing the system to transmit only the refined motion data rather than processing complete frames during transmission.
3Productivity
If patches are compared between frames to generate motion refinement data, then transmission efficiency is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by comparing only the necessary patch regions between frames to generate motion refinement data, rather than processing every possible pixel and region. By focusing the comparison on patches that actually contain motion information and using auxiliary data to guide the matching process, the system reduces processing time while maintaining transmission efficiency.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing motion estimation. In some implementations, a method includes generating a segmentation of point cloud data based on continuity data of the point cloud data. A representation of the segmented point cloud data is projected onto sides of a three-dimensional bounding box. Patches are generated based on the projected representation of the segmented point cloud data. A first frame of the patches is generated. First and second auxiliary information is generated using the first frame and a reference frame. A first patch from the first frame is identified that matches a patch from the reference frame based on the first and second auxiliary information. A motion vector candidate is generated between the first and second patch based on a difference between the first and second auxiliary information. Motion compensation is performed using the motion vector candidate.