Point Cloud Motion Estimation Using GPS for Better Compression
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Solution Overview
Problem
Existing point cloud compression systems face inefficiencies due to inaccurate estimation of rotational matrices and translation vectors, leading to distortion and reduced coding efficiency.
Innovation Solution
Utilize global positioning system information to enhance motion compensation by determining accurate rotational and translation parameters, improving the estimation of motion vectors for point cloud frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional motion estimation methods are used without GPS information, then the processing complexity is lower, but the accuracy of rotational matrix and translation vector estimation is insufficient leading to distortion
Solution Approach 1:
The patent introduces GPS information as an intermediary element to bridge the gap between camera position and motion parameters. By using GPS coordinates and satellite positioning data as an intermediate reference system, the patent enables accurate estimation of rotational matrices and translation vectors without directly complexifying the core motion estimation algorithm. The GPS data serves as a mediator that provides reliable ground truth for motion parameter calculation.
Solution Approach 2:
The patent performs preliminary actions by pre-processing GPS information and pre-establishing reference frames before the actual motion estimation. By preparing the GPS data structure, pre-calculating transformation matrices, and establishing the reference coordinate system in advance, the patent reduces the computational burden during real-time motion estimation while maintaining high accuracy in rotational and translation parameter calculation.
2Productivity
If inaccurate motion parameters are used, then the coding process is simpler, but distortion increases and coding efficiency decreases
Solution Approach 1:
The patent implements feedback mechanisms by continuously comparing the estimated motion parameters with GPS-derived reference values and adjusting the encoding process accordingly. The system uses the accuracy of motion compensation as feedback to optimize coding decisions, ensuring that high precision in motion parameters directly translates to improved coding efficiency by reducing residual distortion and improving prediction accuracy.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting encoding parameters based on the quality of motion compensation. When GPS information provides high-precision motion parameters, the system changes encoding settings to exploit this accuracy, such as adjusting quantization levels, modifying prediction strengths, or changing block sizes to optimize coding efficiency for the specific motion characteristics detected through accurate parameter estimation.
3Measurement precision
If local node motion estimation is applied to all nodes, then the visualization quality improves, but the processing time increases
Solution Approach 1:
The patent applies segmentation by dividing the point cloud into hierarchical levels or regions based on motion characteristics. Instead of uniformly applying local node motion estimation to all nodes, the system segments the data into groups that can be processed differently - applying detailed local estimation only to nodes where it is most needed (e.g., nodes with significant motion variation) while using coarser estimation or global compensation for nodes with consistent motion patterns, thereby reducing overall processing time while maintaining visualization quality where critical.
Data Source
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AI summary
A device for encoding point cloud data, the device comprising: a memory to store the point cloud data; and one or more processors coupled to the memory and implemented in circuitry, the one or more processors configured to identify a first set of global motion parameters from global positioning system information. The one or more processors are further configured to determine, based on the first set of global motion parameters, a second set of global motion parameters to be used for global motion estimation for a current frame and apply, based on the second set of global motion parameters, motion compensation to a reference frame to generate a global motion compensated frame for the current frame.