Explore MATLAB source code curated for "特征融合" with clean implementations, documentation, and examples.
MATLAB implementation of canonical correlation analysis for multivariate data processing including feature dimensionality reduction, feature fusion, and correlation analysis, featuring configurable parameters and modular code structure.
MATLAB code implementation of Generalized Canonical Correlation Analysis (GCCA) for multivariate data analysis tasks including feature dimensionality reduction, feature fusion, and correlation analysis, with enhanced algorithmic explanations and function descriptions.
MATLAB code implementation of Fisher Linear Discriminant Analysis (FLDA) for multivariate data analysis, including feature dimensionality reduction, feature fusion, and correlation analysis with detailed algorithm explanations and computational implementation.
Object tracking program code based on fusion of texture and edge orientation features, developed within the Mean Shift framework with kernel density estimation implementation
This code implements covariance tracking for visual object tracking research, which integrates multiple spatiotemporal features into a unified model. The approach demonstrates strong robustness in visual tracking applications and maintains computational efficiency since its dimensionality equals the number of features used rather than their individual dimensions, resulting in lower complexity and better real-time performance.
Canonical Correlation Analysis code for multivariate data processing techniques including feature dimensionality reduction, feature fusion, and correlation analysis (commonly used mathematical modeling algorithms)
Image fusion technique combining features from two images through wavelet decomposition and multiple fusion methods, with code implementation details for wavelet transformation and fusion algorithms.
MATLAB code implementation of Discriminative Canonical Correlation Analysis (DCCA) for multivariate data analysis including feature dimensionality reduction, feature fusion, and correlation analysis.
MATLAB-based pedestrian detection system integrating HOG (Histogram of Oriented Gradients) and LBP (Local Binary Pattern) features with code implementation details