3D Identity-Invariant Feature Mixing for Animation Consistency
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Solution Overview
Problem
Current systems for animating objects using 3D rendering methods face challenges with timewise consistency and effective resolution, often requiring additional rendering computations to achieve desired animation quality, particularly when transferring movements from one object to another.
Innovation Solution
A system and method that utilize machine-learning models to extract and mix 3D identity-invariant features from source and driver objects, generating a mixing function to produce high-quality animated images by applying this function to the extracted features, resulting in an output image that depicts a target object with enhanced quality and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If graphical techniques such as object swapping or face swapping are applied to animate a first object according to movement of a second object, then animation can be produced, but the output animation exhibits poor timewise consistency and poor effective resolution
Solution Approach 1:
The patent segments the animation generation process into multiple independent components: extracting 3D motion features from the driver object, extracting identity features from the puppet object, computing blending weights based on temporal consistency, and reconstructing the final animation. This segmentation allows each component to be optimized independently, improving both timewise consistency through dedicated temporal weighting and effective resolution through specialized feature extraction networks.
Solution Approach 2:
The patent transforms the animation problem from direct image manipulation to parameter-space operations. By extracting and manipulating 3D motion parameters and identity parameters separately, then blending them through computed weights, the system achieves superior timewise consistency and effective resolution compared to direct pixel-level swapping techniques.
2Manufacturing precision
If additional rendering computations are applied to achieve desired quality of animation video, then animation quality improves, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts essential 3D motion features and identity features from input videos and images, separating the critical quality-determining parameters from the full rendering process. By working with extracted feature representations rather than complete high-resolution images throughout processing, the system achieves high animation quality while significantly reducing computational complexity.
Solution Approach 2:
The patent performs preliminary extraction of 3D motion features and identity features before the main animation synthesis. This preliminary action prepares optimized feature representations that accelerate subsequent blending and rendering operations, reducing overall computational requirements while maintaining animation quality.
3Productivity
If object swapping or face swapping techniques are used to transfer movement between objects, then animation can be generated, but the output exhibits poor timewise consistency
Solution Approach 1:
The patent implements a feedback mechanism by computing blending weights that explicitly account for temporal consistency. The system continuously monitors temporal relationships between consecutive frames and adjusts the blending of motion features accordingly, ensuring that the animated output maintains smooth temporal transitions and consistent timing throughout the animation sequence.
Data Source
AI summary
A system and method of animating an image of an object by extracting a plurality of three dimensional (3D) features from a first image, depicting a puppet object, and from the second image of a driver object, obtaining, a value of a first 3D identity-invariant feature of the puppet object, and a value of a second 3D identity-invariant feature, from the second image, calculating and applying, a mixing function, on the plurality of 3D features, generating a rendered image, based on the plurality of 3D features, the first 3D identity-invariant feature and the second 3D identity-invariant feature, and generating an output image based on the rendered image, the plurality of 3D features, the first image and the second image, wherein the output image depicting a target object comprising at least one 3D identity-invariant feature of the driver object.