Motion Object Detection Algorithm Based on Gaussian Model
This is a motion object detection algorithm utilizing Gaussian modeling, implemented in YUV color space for enhanced color processing and computational efficiency.
Rao-Blackwellised Particle Filtering Implementation for Dynamic Conditionally Gaussian Models
MATLAB implementation of Rao-Blackwellised Particle Filter (RBPF) for Dynamic Conditionally Gaussian Models with comprehensive algorithm explanations and code structure details
Gaussian Models in Pattern Recognition
Gaussian Models in Pattern Recognition - A Practical MATLAB Implementation with Code Examples and Algorithm Explanation
Gaussian Model-Based Background Subtraction in MATLAB
Implementation of Gaussian Model Background Removal in MATLAB for Image Processing Applications
Bayesian Pattern Recognition Using Gaussian Models for Breast Cancer Data
Implementation of Bayesian pattern recognition on the University of Wisconsin's long-term breast cancer dataset using Gaussian models, achieving over 95% recognition rate. This serves as a significant case study in pattern recognition with practical medical applications.
Skin Color Model-Based Face Detection
A face detection program utilizing skin color modeling, which establishes a similarity function through Gaussian modeling, performs binarization using an optimal threshold method, and applies morphological processing to extract face regions. The implementation involves probability density estimation for skin tone classification and image processing techniques for region refinement.
Building a Gaussian Model for Skin Color Distribution in YCbCr Color Space
Constructing a Gaussian model for skin color distribution in YCbCr color space to obtain skin probability likelihood images, followed by skin region segmentation using an optimal dynamic threshold selection algorithm.
GMM Background Modeling with Video Processing
This implementation extends the original BMP framework to process video streams. The MATLAB code establishes 3-5 Gaussian mixture models, performs real-time frame matching, and continuously updates the models for dynamic background modeling. The algorithm handles image processing tasks through probabilistic foreground detection. If you believe this code infringes upon any rights, please contact me for discussion.
Gaussian Models in Pattern Recognition
Gaussian Models in Pattern Recognition with MATLAB Implementation