Face Recognition Algorithm Implementation Using Sparse Representation

This source code implements a face recognition algorithm based on sparse representation, utilizing GPSR (Gradient Projection for Sparse Reconstruction) as the l1-norm minimization method for efficient sparse coding and pattern recognition.

Robust Face Recognition Based on Sparse Representation

This algorithm utilizes minimization techniques to represent test images as sparse linear combinations of training images plus sparse errors caused by occlusion. The method operates directly on raw image data without requiring dimensionality reduction, feature selection, synthetic training instances, or domain-specific information, achieving state-of-the-art performance. Key implementation aspects include L1-norm optimization for sparse coding and robust error correction mechanisms.