MATLAB Implementation of GMM for Gaussian Mixture Background Modeling

Implementing Gaussian Mixture Models (GMM) for background modeling in MATLAB provides a robust approach for video analysis. This algorithm processes input video sequences to separate foreground objects from the background, producing binary segmentation maps and reconstructed background videos. The implementation includes detailed code comments explaining critical steps such as Gaussian component initialization, pixel classification using Mahalanobis distance, and model parameter updates using an adaptive learning rate mechanism. By thoroughly documenting the algorithm workflow and mathematical foundations, this implementation helps beginners understand concepts like expectation-maximization for parameter estimation, background maintenance strategies, and threshold selection for foreground detection. This method effectively supports video background modeling and segmentation, providing a foundation for subsequent video processing and analysis tasks through clear code structure and algorithmic explanations.