Variable Face Model Approximation for Realistic 3D Avatars
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Solution Overview
Problem
Existing video conference systems lack effective methods for generating avatars that accurately represent participants in a virtual 3D environment, failing to account for gaze direction and head orientation, which affects the realism and immersion of the virtual experience.
Innovation Solution
A method and system for generating avatars in a 3D video conference environment that utilizes gaze direction and head orientation information to update participant representations, incorporating neural networks for facial expression estimation and synchronization with audio, and compressing data to optimize bandwidth and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If avatar generation methods are simplified for ease of implementation, then device complexity is reduced, but manufacturing precision of the avatar representation deteriorates
Solution Approach 1:
The patent transforms the complex 3D avatar generation problem into a 2D image generation task by changing the dimensional parameters. The system uses 2D images as input and generates 2D avatar representations, avoiding the complexity of full 3D modeling while maintaining sufficient visual fidelity for video conferencing applications.
Solution Approach 2:
The system creates simplified 2D copies or representations of the participant's appearance rather than generating complete 3D models. These 2D avatar images serve as sufficient copies for the intended purpose of virtual presence in video conferences, eliminating the need for complex 3D reconstruction.
2Reliability
If detailed facial expression and gaze tracking are implemented, then realism of the avatar is improved, but device complexity increases
Solution Approach 1:
The system uses a unified 2D image generation approach that handles multiple functions (facial expressions, gaze direction, head orientation) through a single computational pathway. Rather than implementing separate complex tracking systems for each parameter, the neural network processes all these variations simultaneously through 2D image transformation.
Solution Approach 2:
The patent replaces traditional mechanical or algorithmic approaches to facial expression and gaze tracking with a neural network-based image generation system. This substitution uses learned patterns from training data to automatically capture realistic facial variations without requiring explicit mechanical tracking of each facial parameter.
3Manufacturing precision
If high-resolution avatar data is transmitted, then manufacturing precision of representation is improved, but bandwidth requirements increase
Solution Approach 1:
The system generates lightweight 2D images that can be quickly transmitted and discarded (regenerated for each frame) rather than transmitting large 3D model datasets. These temporary 2D representations provide sufficient visual quality for real-time conferencing without requiring persistent high-resolution 3D data storage or transmission.
Data Source
AI summary
A method for creating a variable model of a face of a person, the method comprises: obtaining a non-riggable model of the face of the person; performing a first approximation process that comprises generating an intermediate variable model that approximates the non-riggable model, using an interactive variable model infrastructure; wherein the generating comprises iteratively changing shape parameters of the intermediate model until fulfilling a proximity condition; and performing a second approximation process that comprises generating the variable model, by iteratively modifying vertices.