Eyelid Spatio-Temporal Reconstruction via Optical Flow Correction
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Solution Overview
Problem
Current methods face challenges in accurately capturing and representing the eyelid region in 3D modeling due to skin deformation, wrinkling, self-shadowing, inter-reflections, and partial occlusions, making it difficult to create a digital representation that accurately conveys facial expressions.
Innovation Solution
A computer-implemented method for spatio-temporal reconstruction of the eyelid using image input data, including depth maps, wrinkle probability data, and optical flow data, to track visible skin areas and generate plausible wrinkle features, correcting optical flow, and integrating with face mesh data for accurate digital representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used to create digital representations of eyelids, then accuracy can be improved, but productivity deteriorates due to labor intensity
Solution Approach 1:
The patent replaces manual mechanical processes with an automated computer-implemented method. The system uses image processing, optical flow analysis, and automatic wrinkle detection algorithms to reconstruct eyelid geometry and deformation, eliminating the need for manual digitization while maintaining high accuracy in representing eyelid features including wrinkles and folds.
Solution Approach 2:
The system enables self-service by automatically processing input images to generate digital eyelid representations without human intervention. The algorithm autonomously detects wrinkles, tracks skin deformation, and reconstructs 3D eyelid geometry from 2D images, allowing the process to serve itself rather than requiring manual operation.
2Manufacturing precision
If detailed tracking of visible skin areas and wrinkle generation is performed, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the eyelid reconstruction process into distinct computational modules: image input processing, optical flow computation, wrinkle detection, visible skin area tracking, and 3D geometry reconstruction. Each module handles a specific aspect of the problem, making the overall complex system manageable and allowing for optimized processing of each individual component.
Solution Approach 2:
The system introduces intermediate data structures and processing stages, such as optical flow fields and wrinkle probability maps, that mediate between the input images and the final 3D reconstruction. These intermediaries break down the complex transformation into manageable steps, each operating on well-defined data formats with clear relationships.
Data Source
AI summary
Methods and systems of reconstructing an eyelid are provided. A method of reconstructing an eyelid includes obtaining one or more images of the eyelid, generating one or more image input data for the one or more images of the eyelid, generating one or more reconstruction data for the one or more images of the eyelid, and reconstructing a spatio-temporal digital representation of the eyelid using the one or more input image data and the one or more reconstruction data.