Secondary Motion Estimation via Local Patch Features
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Solution Overview
Problem
Existing technologies for animating three-dimensional characters in visual effects and video game animation lack accuracy in estimating secondary motion, are computationally intensive, and negatively impact user experience due to high resource consumption and limitations in handling complex calculations and mesh topologies.
Innovation Solution
The method involves estimating secondary motion at the patch level of a volumetric mesh using a deep neural network, considering primary motion data, material properties, and constraint data, which allows for accurate prediction of overall secondary motion and reduces computational complexity by operating on local patches rather than the entire mesh.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing technologies are used to animate three-dimensional characters, then basic movement can be achieved, but secondary motion estimation is inaccurate and computationally intensive
Solution Approach 1:
The patent divides the volumetric mesh into multiple local patches, where each patch is independently processed to estimate secondary motion. This segmentation allows the system to focus computational resources on local regions rather than processing the entire mesh globally, thereby improving estimation accuracy while reducing overall computational complexity.
Solution Approach 2:
The patent applies different processing approaches to different regions by evaluating secondary motion at the patch level with unique feature sets for each patch. This local quality approach enables more accurate secondary motion estimation in regions where it matters most while using fewer computational resources in less critical areas.
2Reliability
If existing technologies process entire mesh globally, then comprehensive motion coverage is achieved, but computational resource consumption is high
Solution Approach 1:
By segmenting the mesh into local patches and processing each patch independently, the patent reduces the computational burden from processing the entire mesh to processing smaller, manageable regions. This maintains reliable motion prediction within each patch while significantly reducing overall computational resource consumption.
Solution Approach 2:
The patent applies secondary motion estimation selectively at the patch level rather than uniformly across the entire mesh. This partial action approach focuses computational effort where it provides the most value, achieving reliable motion prediction with reduced resource consumption.
3Ease of operation
If existing technologies use global processing methods, then overall motion is captured, but user experience is degraded due to high resource usage
Solution Approach 1:
The patent segments the processing into independent patch-level operations that can be executed more efficiently and with lower resource consumption. This improves productivity by reducing the computational overhead associated with global processing methods, thereby enhancing user experience.
Solution Approach 2:
The patent changes the processing parameter from global mesh-level operations to local patch-level operations. This parameter change enables more efficient processing with reduced resource consumption, improving both productivity and user experience.
Data Source
AI summary
Various disclosed embodiments are directed to estimating that a first vertex of a patch will change from a first position to a second position (the second position being at least partially indicative of secondary motion) based at least in part on one or more features of: primary motion data, one or more material properties, and constraint data associated with the particular patch. Such estimation can be made for some or all of the patches of an entire volumetric mesh in order to accurately predict the overall secondary motion of an object. This, among other functionality described herein resolves the inaccuracies, computer resource consumption, and the user experience of existing technologies.