Animation Prediction Model Refines Motion Capture Scenes
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Solution Overview
Problem
Current motion capture technologies lack an efficient method to streamline the process from capturing subject motions and sounds to generating final compiled animation scenes, requiring manual refinement and integration of entity information and animation parameters.
Innovation Solution
A system comprising hardware processors, sensors, and electronic storage that captures motion and sound, generates output signals, and uses machine-readable instructions to train an animation prediction model, which refines initial animation scenes into final compiled scenes by integrating entity and tuning information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual refinement and integration methods are used for motion capture to animation generation, then animation quality can be controlled, but the process efficiency and productivity are reduced
Solution Approach 1:
An animation prediction model serves as an intermediary between motion capture data and final animation scenes. The model automatically predicts refinements needed for initial compiled animation scenes based on preliminary animation information, entity information, and tuning information, reducing manual intervention while maintaining quality control
Solution Approach 2:
The system implements feedback by training the animation prediction model using pairs of initial and final compiled animation scenes along with their associated preliminary animation information. This feedback loop enables the model to learn and improve its predictions, automating the refinement process while preserving quality standards
2Manufacturing precision
If comprehensive entity information and tuning information are integrated into initial compiled animation scenes, then animation quality and precision are improved, but the complexity of the system increases
Solution Approach 1:
The system segments animation information into distinct components: preliminary animation information (entity definitions, motion capture data, tuning parameters), initial compiled animation scenes, and final compiled animation scenes. This segmentation allows for systematic processing and integration without overwhelming system complexity
Solution Approach 2:
The system performs preliminary actions by organizing and storing entity information and tuning information before generating initial compiled animation scenes. This preliminary preparation enables more efficient integration and refinement processes, as the necessary information is already structured and available
Data Source
AI summary
Systems and methods configured to facilitate animation generation are disclosed. Exemplary implementations may: capture via one or more sensors motion and/or sound made by one or more subjects in physical space and generate output signals conveying information related to the motion and/or the sound made by individual ones of the one or more subjects; store, in electronic storage, final compiled animation scenes, initial compiled animation scenes corresponding to the final compiled animation scenes, preliminary animation information associated with the final compiled animation scenes, and input refinement information; and train, from the final compiled animation scenes, the initial compiled animation scenes corresponding to the final compiled animation scenes, the preliminary animation information, and the input refinement information, an animation prediction model.