Automated Eyeball Positioning in 3D Head Meshes
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Solution Overview
Problem
Conventional methods for 3D head modeling, particularly in virtual reality and gaming, face challenges in accurately positioning and refining the eyeball region of 3D meshes due to high specular reflections and occlusions, requiring significant manual effort and prone to errors.
Innovation Solution
An electronic device and method for automated eyeball positioning using a 3D template mesh, which involves extracting feature points from images, fitting a sphere, estimating initial and final pose transformations, and interpolating points to accurately position the eyeball within the 3D mesh, reducing manual intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual refinement of the 3D mesh is performed, then the accuracy of eyeball positioning is improved, but the time and effort required increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-defining a template mesh with properly positioned eyeballs before the actual 3D reconstruction process. This template is prepared in advance and then automatically applied to the reconstructed mesh, eliminating the need for manual eyeball positioning and refinement after reconstruction.
Solution Approach 2:
The patent uses copying by creating a standardized template mesh that contains pre-positioned eyeballs with correct anatomical relationships. This template is then copied and applied to the reconstructed 3D head mesh, transferring the accurate eyeball positioning without requiring manual intervention for each new reconstruction.
2Productivity
If automated methods are used for eyeball positioning, then the time required is reduced, but the accuracy and quality of positioning deteriorates
Solution Approach 1:
The patent uses copying by creating a standardized template mesh that contains pre-positioned eyeballs with correct anatomical relationships. This template is then copied and applied to the reconstructed 3D head mesh, transferring the accurate eyeball positioning without requiring manual intervention for each new reconstruction.
Solution Approach 2:
The patent applies parameter changes by using registration techniques that align the template mesh with the reconstructed mesh based on anatomical landmarks. This alignment process automatically adjusts the position, orientation, and scale parameters of the template to match the specific characteristics of each reconstructed head, ensuring accurate eyeball positioning for varying geometries.
3Extent of automation
If 3D reconstruction methods are used, then the modeling process is automated, but errors and artifacts appear in the eye region
Solution Approach 1:
The patent applies taking out by separating the eyeball positioning task from the overall 3D reconstruction process. Instead of attempting to reconstruct eyeballs directly from images (which causes errors), the method extracts the head geometry through reconstruction, then separately applies a pre-defined template mesh that contains accurately modeled eyeballs, effectively removing the problematic reconstruction step for the eye region.
Solution Approach 2:
The patent uses copying by creating a standardized template mesh that contains pre-positioned eyeballs with correct anatomical relationships. This template is then copied and applied to the reconstructed 3D head mesh, transferring the accurate eyeball positioning without requiring manual intervention for each new reconstruction.
Data Source
AI summary
An electronic device and method for positioning an eyeball into a 3D mesh of a head portion of an object is provided. Images of an eye of an object, the 3D mesh of the head portion of the object, and a 3D template mesh of an eyeball are acquired. 3D feature points for eye regions are extracted from the images and fit to a sphere. An initial pose transformation between the 3D template mesh and the sphere is estimated. Based on the 3D template mesh, a first set of points corresponding to the eye regions are interpolated. Based on sampling parameters for the first set of points, a second set of points are determined. A final pose transformation is determined based on minimization of difference between the first and the second set of points and the 3D template mesh is fit into an eyeball socket of the 3D mesh.