Face and Expression Recognition

Face and Expression Recognition is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 42k research works in it since 1951. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of various machine learning and dimensionality reduction techniques to the field of face recognition. It covers topics such as feature selection, support vector machines, ensemble methods, local binary patterns, non-negative matrix factorization, spectral clustering, Laplacian eigenmaps, and sparse representation in the context of face recognition.

• Face Recognition
• Dimensionality Reduction
• Feature Selection
• Support Vector Machines
• Ensemble Methods
• Local Binary Patterns
• Non-negative Matrix Factorization
• Spectral Clustering
• Laplacian Eigenmaps
• Sparse Representation