Video-Driven Graphical Object Animation Control
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Solution Overview
Problem
Computer animators face impracticality in setting control values for every frame of an animation, especially when trying to replicate real-world movements and expressions in digital characters, as manually recreating or interpolating values for each frame is labor-intensive and time-consuming.
Innovation Solution
A method that involves selecting key frames in a calibration video stream, defining animation control values, parameterizing features, deriving distance vectors, mapping these vectors into control variables, and applying the mapping operation to an actual performance video stream to generate a time sequence of animation control values, which are then used to animate a graphical object, allowing for automated animation driven by real-life video performance while maintaining artistic control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manually setting control values for every frame of animation, then animation precision and control are improved, but time consumption and labor intensity increase significantly
Solution Approach 1:
The patent uses video performance capture to copy real-world actor movements and expressions directly onto digital characters. The system extracts motion data from video frames and automatically maps it to control variables of the graphical object, eliminating the need for manual frame-by-frame animation while preserving the essence of the performance.
Solution Approach 2:
The patent replaces the manual mechanical process of setting control values for each frame with an automated computational system. The system uses video processing algorithms, parameter extraction, and mathematical modeling to automatically generate animation control values from video input, substituting human manual operation with computational automation.
2Ease of operation
If using controls for animation instead of rebuilding models for every frame, then ease of operation is improved, but animation quality and realism may deteriorate
Solution Approach 1:
The system copies real-world performance data from video directly into the animation control system. By extracting actual motion parameters from video frames and mapping them to the character's control variables, the system maintains high animation quality and realism while preserving the ease of automated operation.
Solution Approach 2:
The patent transforms video data into animation control parameters through a systematic parameter extraction and mapping process. The system converts video frame data into a set of control variable values that directly drive the graphical object's animation, ensuring high quality while maintaining operational ease.
3Extent of automation
If parameterizing features of the actor to obtain parameter vectors for each frame, then animation automation capability is improved, but computational complexity increases
Solution Approach 1:
The patent segments the complex video data into discrete parameter vectors representing key features of the actor's performance. By breaking down the video analysis into separate parameter extraction steps (position, orientation, expression, etc.), the system manages computational complexity while maintaining high automation capability.
Solution Approach 2:
The system performs preliminary parameter extraction and distance vector calculation during a calibration phase using training data. This preliminary processing creates lookup tables and mapping relationships that can be quickly applied during actual animation generation, reducing real-time computational complexity while maintaining automation.
Data Source
AI summary
A method and system for driving a graphical object based on a performance of an actor in a video stream. A plurality of key frames are selected in a calibration video stream, allowing animation control values to be defined, in accordance with artistic intent, for each of a set of control variables, corresponding to each of the key frames. Features of the actor in the calibration video stream are parameterized so as to obtain a vector of values of parameters for each frame of the calibration video stream, and, then, an array of distance vectors is derived, characterizing a distance between each pair of vectors of values of parameters among the video stream frames. The space of distance vectors is mapped into the set of control variables according to a mapping operation which is then applied to distance vectors derived from an actual performance video stream to obtain a time sequence of animation control values. Finally, an animation is created on the basis of applying the sequence of animation control values to the graphical object.