Motion Capture Reconstruction Render Farm Partitioning
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Solution Overview
Problem
Conventional motion capture systems face inefficiencies and downtime due to the large size of motion capture beat files, which exceed the manageable input volume for reconstruction processing, often requiring extensive resources for recovery.
Innovation Solution
A reconstruction render farm (RRF) is implemented to automatically partition large motion capture files into smaller subsets, distributing the processing load across multiple computers, using a motion capture database to determine reconstruction parameters and manage the partitioning and merging of data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion capture beat files are processed as complete units, then reconstruction accuracy is maintained, but processing time and resource requirements increase significantly
Solution Approach 1:
The patent divides large motion capture beat files into smaller partitions that can be processed independently and in parallel. Each partition is reconstructed separately using the same accuracy-preserving algorithms, then the results are merged to form the complete reconstruction. This segmentation enables both maintained accuracy and reduced processing time through parallel computation.
2Reliability
If large motion capture files are processed using conventional systems, then complete data reconstruction is achieved, but system resource requirements and downtime increase
Solution Approach 1:
The system partitions large motion capture files into manageable segments that can be processed simultaneously across multiple computing resources. This approach maintains complete data reconstruction by ensuring all partitions are processed and merged, while significantly improving productivity through parallel processing and reduced system downtime.
Solution Approach 2:
After individual partitions are reconstructed in parallel, the system merges the results into a complete reconstruction. This merging process ensures data completeness and reliability while the parallel processing approach maintains high productivity and reduces overall processing time.
3Productivity
If motion capture data is processed in smaller units, then processing efficiency improves, but data continuity and completeness may be compromised
Solution Approach 1:
The patent implements segmentation into smaller processing units while maintaining data continuity through careful partition design. Each partition contains complete temporal and spatial information necessary for independent reconstruction, and the merging process preserves the continuous nature of the motion capture data by aligning partitions according to their temporal sequences and spatial relationships.
Data Source
AI summary
Motion capturing markers coupled to at least one motion capture object, comprising: generating a plurality of Configurations, each Configuration including partitioning parameters; partitioning a motion capture beat into beat partitions using the plurality of Configurations; reconstructing the beat partitions, wherein each beat partition is reconstructed using each Configuration and corresponding motion capture camera calibration information to generate point data representing a marker; and merging the point data to form at least one master point file.