Automatic 3D Object Rigging via Transformer Constraint Graphs
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Solution Overview
Problem
The challenge in computer graphics and virtual experiences is the manual and time-consuming process of rigging physics-based 3D objects, such as vehicles, which requires assigning joints and physics-based rigid bodies to simulate realistic motion.
Innovation Solution
A system and method for automatically rigging physics-based 3D objects using a computer-implemented method that involves segmenting a 3D mesh into sub-meshes, determining a constraint graph using a transformer model, and calculating parameters based on objective functions to simulate motion in a virtual environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual rigging is performed for physics-based 3D objects, then the simulation accuracy and realism are improved, but the time and effort required increase significantly
Solution Approach 1:
The system performs automatic rigging by analyzing the 3D mesh structure and generating constraint graphs independently without requiring manual intervention. The automated pipeline segments the mesh, identifies rigid bodies, determines joints and constraints, and calculates parameters to produce a fully rigged model ready for physics simulation.
Solution Approach 2:
The patent replaces the manual mechanical process of rigging with an automated computational system using transformer models and constraint graphs. The transformer model processes 3D mesh data and generates rigging parameters automatically, substituting human expertise with an AI-based system.
2Productivity
If automatic rigging is implemented, then the time and effort required are reduced, but the complexity of the system increases
Solution Approach 1:
The system segments the 3D mesh into multiple rigid bodies and identifies separate components that need to be connected through joints. This segmentation allows the complex rigging problem to be broken down into manageable steps: mesh processing, rigid body identification, joint determination, and constraint calculation.
Solution Approach 2:
The transformer model acts as an intermediary between the input 3D mesh and the output rigging parameters. It processes the mesh data through intermediate representations and generates the constraint graphs and parameters, simplifying the overall system architecture by using a single powerful model to handle multiple rigging tasks.
3Manufacturing precision
If manual rigging is performed, then the precision and control over the rigging process are maintained, but the productivity decreases
Solution Approach 1:
The system uses objective functions to evaluate the quality of generated rigging parameters and provides feedback to refine the results. The transformer model can be trained on labeled data to improve its accuracy, and the optimization process can adjust parameters based on simulation results to achieve precise rigging.
Solution Approach 2:
The system automatically determines and optimizes multiple parameters including joint types, constraint values, and rigid body properties. By changing and optimizing these parameters automatically based on the mesh geometry and physics requirements, the system achieves precision comparable to manual rigging while maintaining high productivity.
Data Source
AI summary
Implementations relate to methods, systems, and computer-readable media to automatically perform rigging of physics-based three-dimensional objects. In some implementations, the method may include obtaining a 3D mesh of a 3D object, segmenting the 3D mesh into two or more sub-meshes, wherein each sub-mesh corresponds to a respective part of the 3D object, determining a constraint graph for the 3D object using a transformer model, wherein the two or more sub-meshes are provided as input to the transformer model, and wherein the constraint graph defines a set of joints such that each joint defines constraints on motion of respective pairs of the parts of the 3D object, and calculating a plurality of parameters for the constraint graph based on one or more objective functions, wherein the sub-meshes, the constraint graph, and the plurality of parameters are usable to simulate motion of the 3D object in a virtual environment.