3D Face Rendering Using Pre-Stored Models and Texture Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D face rendering technologies face complexity and high computational demands due to the need for intricate calculations and large data processing, especially when generating and adjusting 3D face models for realistic representation.
Innovation Solution
A method and device utilizing a dual-camera system to capture depth and color information, detecting 2D facial feature points, matching them with pre-stored 3D models, and generating skin texture maps to construct and render 3D faces efficiently, with optional depth information acquisition using structured-light sensors for real-time reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional 3D face rendering methods are used, then realistic 3D face models can be generated, but the process involves complicated operations and large computational pressure
Solution Approach 1:
The patent applies preliminary action by pre-storing multiple 3D face models in advance. Instead of generating a 3D face model in real-time through complex rendering operations, the system pre-prepares a library of 3D face models with various characteristics. When a recognition task is performed, the system directly selects and matches from these pre-stored models, significantly reducing the computational complexity and operational steps required during actual use while maintaining the realism quality of the 3D face representations.
2Manufacturing precision
If traditional 3D face rendering methods are used, then realistic 3D face models can be generated, but there is a large amount of calculation and high computational pressure
Solution Approach 1:
The patent applies preliminary action by pre-storing multiple 3D face models in advance. Instead of generating a 3D face model in real-time through complex rendering operations, the system pre-prepares a library of 3D face models with various characteristics. When a recognition task is performed, the system directly selects and matches from these pre-stored models, significantly reducing the computational complexity and operational steps required during actual use while maintaining the realism quality of the 3D face representations.
3Measurement precision
If 2D to 3D conversion is performed through complex operations, then accurate 3D face models can be obtained, but the process time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-storing multiple 3D face models in advance. Instead of generating a 3D face model in real-time through complex rendering operations, the system pre-prepares a library of 3D face models with various characteristics. When a recognition task is performed, the system directly selects and matches from these pre-stored models, significantly reducing the computational complexity and operational steps required during actual use while maintaining the realism quality of the 3D face representations.
Solution Approach 2:
The patent applies copying by using pre-stored 3D face models as templates or copies that can be directly matched against 2D input images. Rather than performing complex real-time 2D-to-3D conversion, the system creates a correspondence between 2D facial features and pre-existing 3D model copies, significantly reducing processing time while maintaining accuracy through the use of high-quality pre-rendered 3D representations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies the 3D face acquisition process, improves rendering efficiency, and enhances the realism of 3D face models by merging skin texture maps with pre-stored or reconstructed 3D models, while optimizing resource utilization and reducing computational complexity.
Implementation Method 1
depth information of a face is acquired using a structured-light sensor
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
The present disclosure provides a method and a device for acquiring a 3D face. The method includes: detecting a 2D face image captured from a front side to acquire 2D facial feature points; matching the 2D facial feature points with facial feature points of a pre-stored 3D face model; and in response to that the 2D facial feature points match the facial feature points of the pre-stored 3D face model, acquiring a skin texture map, and rendering the pre-stored 3D face model with the skin texture map to acquire the 3D face.