Explore MATLAB source code curated for "人脸特征" with clean implementations, documentation, and examples.
Dual-view 3D facial reconstruction using frontal projection and horizontal rotation views under orthographic projection model, with getfeature function for landmark annotation on facial images
Implementation of LDA for face feature extraction and recognition using MATLAB, including code development and comprehensive result analysis with performance metrics
The LBP (Local Binary Pattern) algorithm was initially developed for texture description and later adapted for facial analysis to characterize facial features using efficient pixel-value comparisons and binary encoding.
The LBP (Local Binary Pattern) algorithm was initially developed for texture description and later adapted for facial feature characterization in computer vision applications.
Detecting human faces and extracting facial characteristics using computer vision algorithms
This MATLAB program framework implements face feature extraction using LDA (Linear Discriminant Analysis) and PCA (Principal Component Analysis) pattern recognition methods, offering excellent performance for facial recognition applications.
This project implements Principal Component Analysis (PCA) for facial feature extraction and employs Support Vector Machine (SVM) multi-class classifier for face recognition, complete with an intuitive user interface for image input and processing.