3D Head Reconstruction From 2D Video for Immersive Conferencing
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Solution Overview
Problem
Existing two-dimensional electronic communication, such as videoconferencing, fails to replicate the immersion and non-verbal cues of in-person interactions, and existing 3D communication methods, like animated avatars, do not effectively recreate realistic, real-time representations of conference participants.
Innovation Solution
A method using artificial neural networks to reconstruct photo-realistic, 3D representations of conference participants from 2D or 2.5D image data, incorporating head alignment and depth data to fill in missing areas and apply texture, with systems and media for real-time holographic projection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If two-dimensional videoconferencing is used for electronic communication, then ease of operation is maintained, but immersion and non-verbal communication are insufficient
Solution Approach 1:
The patent transitions from 2D videoconferencing to 3D holographic communication by reconstructing three-dimensional representations of participants from 2D image data. This dimensional transformation enables immersive communication while preserving ease of operation through automated AI-based reconstruction processes.
2Loss of information
If 3D communication methods like animated avatars are used, then immersion is improved, but photo-realistic representation is not achieved
Solution Approach 1:
The patent replaces traditional mechanical 3D modeling methods with AI-based neural networks that automatically generate photo-realistic 3D representations from 2D images. This substitution enables both immersion and photorealistic quality without requiring complex manual 3D scanning or modeling processes.
Solution Approach 2:
The system transforms 2D image parameters into 3D spatial parameters through neural network processing. By changing the dimensional parameters and applying learned transformations from training data, the system generates photorealistic 3D representations that maintain both immersion and visual fidelity.
3Loss of information
If complete 3D reconstruction is performed in real-time, then immersion is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary training of neural networks using extensive 3D image data before real-time operation. This pre-computation enables the system to rapidly reconstruct 3D representations during actual communication without requiring complex real-time calculations, thus reducing device complexity while maintaining immersion.
Solution Approach 2:
The system creates simplified 3D copies or representations of participants using neural networks trained on complete 3D data. These copied representations maintain sufficient photorealistic quality for immersion while requiring less computational complexity than full 3D reconstruction during real-time communication.
Data Source
AI summary
A method and system for reconstructing a photo-realistic, three-dimensional representation of at least part of a conference participant's head from image data, head alignment data, and depth data. The image data is projected from a world space into an object space using the head alignment data and depth data. In the object space, at least part of the area missing from the image data is completed using a computational model of a person. An artificial neural network is used to reconstruct the texture and depth of the reconstruction as part of the completion. At least the image data and the head alignment data are determined based on two-dimensional or 2.5-dimensional images of the conference participant captured by a camera.