1adrianb/2D-and-3D-face-alignment
2D And 3D Face Alignment
This project is a computer vision library designed for facial landmark detection and alignment. It provides a framework for identifying and mapping specific points on a human face in both two-dimensional and three-dimensional space, enabling the normalization of facial geometry and orientation across diverse images.
The system utilizes a deep learning approach to extract precise facial coordinates, supporting tasks such as expression analysis and geometric modeling. By employing a stacked hourglass architecture, the model performs multi-stage feature refinement to capture spatial relationships across multiple scales, ensuring consistent landmark positioning regardless of camera angles.
The library incorporates volumetric landmark estimation to reconstruct the full structure of the face by regressing depth information alongside standard spatial coordinates. It leverages pre-trained neural network parameters to facilitate feature extraction, providing a foundation for biometric data processing and digital character animation workflows.
Features
- Facial Landmark Detection - Identifies and tracks specific points on a human face in two or three dimensions to monitor expressions and movements.
- Volumetric Regression Architectures - Predicts three-dimensional facial points by regressing depth information alongside spatial coordinates to reconstruct facial structure.
- Face Alignment And Reconstruction - Provides tools for facial landmark detection and 3D face modeling to normalize facial positioning.
- Convolutional Neural Network Architectures - Implements a stacked hourglass convolutional neural network architecture to capture spatial relationships across multiple scales.
- Facial Landmark Analysis - Extracts precise facial coordinates to support expression analysis and geometric face modeling.
- Facial Region Alignment - Normalizes facial positioning by adjusting orientation and geometry to ensure consistency across images.
- Refinement Modules - Employs iterative refinement modules to improve landmark localization accuracy based on facial geometry.
- Face Detection and Alignment - Normalizes facial geometry and orientation to ensure consistent landmark positioning across diverse images.
- Facial Landmark Mapping - Maps detected facial landmarks to a 3D coordinate system for object alignment.
