Feature Point Localization via Component Shape Models
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Solution Overview
Problem
Existing methods for localizing facial feature components in images, such as active shape models, struggle with extreme poses, lighting conditions, and expressions, which are common in modern digital images captured by portable cameras.
Innovation Solution
A feature point localization module that applies a profile model and a component-based shape model to determine feature point locations, allowing for the automatic adjustment of feature points based on user input to improve accuracy and reduce user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If standard active shape model (ASM) is used to localize facial feature components, then the method is simple to implement, but it does not handle extreme pose, lighting, and expression conditions well
Solution Approach 1:
The patent segments the face into multiple independent components (eyes, eyebrows, nose, mouth, jawline) and applies profile models to each component separately. This segmentation allows the system to handle extreme poses and expressions more effectively by treating each component independently while maintaining overall facial structure through shape model constraints.
2Measurement precision
If more user interaction is required to adjust feature points manually, then localization accuracy may improve, but user time and effort increase
Solution Approach 1:
The system provides self-service by automatically adjusting other feature points based on the movement of one feature point. When a user moves a single feature point to a fixed location, the shape model automatically recalculates and adjusts the positions of other feature points, eliminating the need for manual adjustment of each point individually while maintaining high localization accuracy.
3Extent of automation
If a component-based shape model is applied to automatically adjust feature points, then user interaction is reduced, but the complexity of the system increases
Solution Approach 1:
The patent merges profile models (which capture local component characteristics) with shape models (which capture global facial structure) into a unified component-based framework. This combination allows automatic adjustment of feature points while managing complexity by integrating local and global constraints in a cohesive system that leverages the strengths of both modeling approaches.
Data Source
AI summary
Various embodiments of methods and apparatus for feature point localization are disclosed. A profile model and a shape model may be applied to an object in an image to determine locations of feature points for each object component. Input may be received to move one of the feature points to a fixed location. Other ones of the feature points may be automatically adjusted to different locations based on the moved feature point.