3D Facial Mesh UV Map Generation for Virtual Image Accuracy
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Solution Overview
Problem
Current face creation technologies in image processing applications suffer from low efficiency and depth distortion issues, as they lack the ability to accurately represent the three-dimensional structure of a real face in generated virtual facial images.
Innovation Solution
An image processing method that constructs a three-dimensional facial mesh from a target image, transforms it into a UV map to carry vertex position data, and uses this data to determine face creation parameters, ensuring the generated virtual facial image accurately matches the three-dimensional structure of the real face.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of face creation parameters is used, then users can customize virtual facial images, but the face creation efficiency is low and time-consuming
Solution Approach 1:
The patent replaces the manual mechanical adjustment system with an automated image processing system. A neural network model automatically extracts facial features from input images and generates face creation parameters, eliminating the need for manual parameter adjustment by users and significantly improving face creation efficiency
Solution Approach 2:
The system enables self-service face creation by automatically processing user-uploaded images to generate virtual facial images. The neural network model autonomously completes the entire parameter extraction and image generation process without requiring user intervention in parameter adjustment, making the service more efficient and user-friendly
2Manufacturing precision
If traditional face creation methods are used, then virtual facial images can be generated, but depth distortion occurs and three-dimensional structure accuracy is poor
Solution Approach 1:
The patent introduces three-dimensional spatial dimension into the face creation process by using a neural network model that processes images in 3D space. The model extracts depth information and spatial relationships from 2D images to generate accurate 3D facial structures, eliminating depth distortion and improving three-dimensional structure accuracy
Solution Approach 2:
The system changes the parameter representation from traditional 2D coordinate-based parameters to 3D spatial parameters including depth, width, and height dimensions. This parameter transformation enables accurate representation of facial three-dimensional structure and eliminates depth distortion in generated virtual facial images
Data Source
AI summary
Embodiments of this application disclose an image processing method performed by a computer device. The method includes: constructing a three-dimensional facial mesh corresponding to a target object according to a target image of the target object; transforming the three-dimensional facial mesh into a target UV map, the target UV map carrying position data of vertices on the three-dimensional facial mesh; determining target face creation parameters according to the target UV map; and generating, on the basis of the target face creation parameters, a target virtual facial image corresponding to the target object. The method can make a three-dimensional structure of a virtual facial image generated by face creation comply with a three-dimensional structure of a real face, thereby improving the accuracy and efficiency of the virtual facial image generated by face creation.