Explore MATLAB source code curated for "人脸表情识别" with clean implementations, documentation, and examples.
MATLAB implementation for facial expression recognition combining Local Binary Pattern (LBP) and Local Phase Quantization (LPQ) algorithms, utilizing Support Vector Machine (SVM) for classification
Implementation of the 2DLDA method for facial expression recognition with specific person identification capabilities
Person-independent recognition using the 2DPCA method in facial expression recognition
Facial micro-expressions reveal crucial insights into human emotions, even when individuals attempt to conceal their feelings. Historically, limited research has been conducted on detecting and recognizing micro-expressions using computer vision techniques. This implementation processes spontaneous micro-expression databases through preprocessing and Haar feature-based image cropping, followed by feature extraction using Local Binary Patterns on Three Orthogonal Planes (LBP-TOP) and Local Gray-Coding Patterns on Three Orthogonal Planes (LGCP-TOP) descriptors. The system employs Support Vector Machines (SVM) for detection and classification, achieving accuracy comparable to existing state-of-the-art methods.
This implementation utilizes an image database where the detection phase begins with grayscale conversion, followed by lighting compensation and noise reduction. Edge detection is then performed, and images are normalized to ensure consistency. For feature extraction, PCA (Principal Component Analysis) is employed to extract facial features and project them into vector space. Finally, the system calculates the nearest distance between test images and reference models to determine the most matching expression category.
Gabor Wavelet Transform for facial expression recognition, generating features across 5 scales and 8 directions. This implementation references the paper "Gabor feature classification using enhanced FLD model facial recognition" and involves convolutional operations with Gabor filter banks for optimized feature discrimination.
Implementation of 2DPCA method for face expression recognition focusing on person-specific identification with code-oriented algorithm explanations.
A Complete Framework for Facial Expression Recognition with Technical Implementation Details