ML Object Alignment for Animation Model Rigging
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Solution Overview
Problem
The production of animated features and computer-generated imagery is hindered by the time-consuming process of creating and modifying geometric descriptions of models, including rigging, animation variables, and other attributes, which requires significant computational resources and manual effort.
Innovation Solution
An automated method using machine learning models to align object representations, allowing for the transfer of information such as textures, rigging, and paint data from a source object to a target object by identifying corresponding points and applying transformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hand-copying information from one model to another is performed, then model information can be reused, but the process still requires significant time and manual effort to place copied data onto correct positions
Solution Approach 1:
The patent replaces the manual mechanical process of placing copied data with an automated computer-implemented algorithm. The system automatically identifies corresponding vertices between source and target models using geometric hashing and transformation matrices, eliminating the need for manual vertex-by-vertex data placement while maintaining accuracy.
Solution Approach 2:
The system enables the target model to automatically acquire and organize copied information through self-adjusting algorithms. The geometric hashing algorithm and transformation matrices allow the target model to autonomously identify corresponding vertices and apply copied data without external manual intervention, making the process self-service oriented.
2Manufacturing precision
If each model is hand-created and set up individually, then model quality and detail can be ensured, but production time and cost increase significantly
Solution Approach 1:
The patent implements automated copying of model information from source to target models using geometric hashing and transformation algorithms. This allows high-quality model details to be replicated across multiple models automatically, maintaining manufacturing precision while dramatically increasing productivity by eliminating manual recreation of identical or similar model elements.
Solution Approach 2:
The system creates a universal framework for model information reuse that can handle multiple target models from a single source model. The geometric hashing algorithm and transformation matrices provide a multi-functional solution that works across different model types and scales, enabling one model to serve multiple purposes and reducing overall production requirements.
3Adaptability or versatility
If models are modified during production to achieve desired attributes, then model adaptability improves, but significant time and effort are required for each modification
Solution Approach 1:
The patent performs preliminary alignment and correspondence identification between source and target models using geometric hashing and transformation matrices before actual data copying occurs. This preliminary action establishes the framework for efficient modification, allowing subsequent attribute changes to be applied quickly without requiring time-consuming manual adjustments during production.
Data Source
AI summary
Techniques for aligning object representations for animation include analyzing a source object representation and a target object representation to identify a category of the source object and a category of the target object. Based on the category or categories of the objects, a feature extraction machine learning models is selected. The source object representation and the target object representation are provided as input to the selected feature extraction machine learning model to generate respective semantic descriptors and shape vectors for the source and target objects. Based on the semantic descriptors and the shape vectors for the source and target objects, an alignment machine learning model generates an aligned target object representation that is aligned with the source object representation and usable for animating the target object.