Deformation Graph Animation Using Tracked Skeleton Data
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Solution Overview
Problem
Computer animation is typically time-consuming and requires specialized expertise and hardware, limiting its accessibility to experienced users, and struggles with animating non-humanoid characters and incomplete surfaces.
Innovation Solution
A method and system that use a deformation graph generated from a mesh, with tracked skeleton data from human body motion to animate objects, allowing for intuitive and rapid animation using consumer hardware, enabling users with little or no expertise to create animations in 2D or 3D.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CG animation methods are used, then animation quality and control can be achieved, but the process becomes extremely time-consuming and requires specialized expertise
Solution Approach 1:
The patent copies human motion data from motion capture sensors and applies it directly to animate objects, replacing the traditional manual keyframe animation process. This allows high-quality animation to be created by copying real human movements rather than manually positioning each bone and vertex, dramatically reducing time while maintaining control precision
Solution Approach 2:
The patent replaces the mechanical system of manual bone weighting and skeleton embedding with an automated system that uses motion capture data and machine learning algorithms. The system automatically maps captured human motion to object animation, eliminating the need for specialists to manually configure complex animation parameters
2Reliability
If traditional animation tools are used, then professional animation results can be achieved, but the complexity of the process increases significantly
Solution Approach 1:
The patent extracts the essential animation function from the complex traditional pipeline by isolating the core task: mapping motion capture data to object vertices. This extraction removes unnecessary intermediate steps like manual skeleton embedding and bone weighting, simplifying the process while maintaining animation quality
Solution Approach 2:
The patent creates a universal animation system that can animate any 3D object regardless of its shape or complexity. The same motion capture data can be applied to different objects without requiring specialized configuration for each case, making the system versatile and reducing overall process complexity
3Measurement precision
If detailed deformation graphs are used to handle complex features, then animation accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary sampling of the 3D mesh to identify important features and high-curvature regions before animation. This pre-processing creates a optimized deformation graph that focuses computational resources on areas that matter, achieving high accuracy without excessive complexity in the overall system
Data Source
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AI summary
Methods of animating objects using the human body are described. In an embodiment, a deformation graph is generated from a mesh which describes the object. Tracked skeleton data is received which is generated from sensor data and the tracked skeleton is then embedded in the graph. Subsequent motion which is captured by the sensor result in motion of the tracked skeleton and this motion is used to define transformations on the deformation graph. The transformations are then applied to the mesh to generate an animation of the object which corresponds to the captured motion. In various examples, the mesh is generated by scanning an object and the deformation graph is generated using orientation-aware sampling such that nodes can be placed close together within the deformation graph where there are sharp corners or other features with high curvature in the object.