3D Avatar Video Generation for Real-Time Expression Sync
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Solution Overview
Problem
Conventional avatar generation methods lack flexibility and fail to reflect real-time changes in facial expressions, leading to identity theft and network security issues due to the lack of unique user identity representation.
Innovation Solution
A method and system for generating a two-dimensional avatar image based on a reference image and a video frame, transforming it into a three-dimensional avatar using multi-modality features, including motion, audio, and text, to create a customized three-dimensional avatar video that aligns with the user's unique features and expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional avatar generation methods are used, then the process is simple, but the avatar lacks flexibility and cannot reflect real-time changes in facial expressions
Solution Approach 1:
The system performs preliminary actions by pre-extracting facial feature points and establishing correspondence between 2D avatar images and 3D models before real-time processing. The facial feature point extraction and matching algorithms are prepared in advance, enabling rapid real-time expression tracking without complex processing during actual avatar generation.
Solution Approach 2:
The system implements dynamics by continuously tracking facial feature points across video frames and dynamically updating the 3D avatar's facial expressions in real-time. The facial feature correspondence relationship allows dynamic mapping of 2D expression changes to 3D avatar movements, enabling flexible real-time adaptation.
2Reliability
If conventional avatar generation methods are used, then the implementation is straightforward, but user privacy cannot be protected due to lack of unique identity representation
Solution Approach 1:
The system applies local quality by extracting and protecting specific local facial feature points rather than processing entire facial images. By focusing on key facial landmarks and their correspondence relationships, the system maintains unique identity representation for privacy protection while avoiding comprehensive biometric data processing.
Solution Approach 2:
The system creates a stylized 2D avatar image that copies essential facial characteristics from the user's reference image. This avatar copy serves as a unique identity representation that protects privacy by not storing or transmitting original biometric data, while still enabling reliable user identification.
3Manufacturing precision
If detailed three-dimensional transformation is performed, then the avatar representation becomes more vivid, but the processing time and computational resources increase
Solution Approach 1:
The system segments the complex 3D transformation process into distinct stages: 2D avatar generation, facial feature point extraction, feature correspondence establishment, and 3D model animation. This segmentation allows each module to be optimized independently, achieving detailed avatar representation while managing processing time through modular computation.
Solution Approach 2:
The system applies partial action by focusing computational resources on key facial feature points rather than processing entire facial surfaces. By tracking only essential landmarks (eyes, nose, mouth corners, etc.) and their correspondence, the system achieves vivid expression representation with reduced computational overhead compared to full-face 3D reconstruction.
Data Source
AI summary
Methods, devices and computer program products for processing video are disclosed herein. A method includes: generating, based on a reference image and a first frame of a video comprising an object, a two-dimensional avatar image of the object; and generating a base three-dimensional avatar of the object by performing a three-dimensional transformation on the two-dimensional avatar image and the object in the first frame. The method further includes: generating a three-dimensional avatar video corresponding to the video based on the base three-dimensional avatar and features of the video, the features comprising differences of the object between adjacent frames of the video. This solution enables the generation of a customized three-dimensional avatar video for an object in a video, where the avatar can move in synchronization with the object and retain the unique features of the object, and can provide a more detailed and vivid representation than a two-dimensional avatar.