Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
Initialization enhancer for non-negative matrix factorization
Engineering Applications of Artificial Intelligence
Fast nonnegative matrix factorization and its application for protein fold recognition
EURASIP Journal on Applied Signal Processing
Nonnegative matrix factorization with quadratic programming
Neurocomputing
Non-negative matrix factorisation for object class discovery and image auto-annotation
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Blind Image Separation Using Nonnegative Matrix Factorization with Gibbs Smoothing
Neural Information Processing
Computational Intelligence and Neuroscience - Advances in Nonnegative Matrix and Tensor Factorization
Robust watermarking based on DWT and nonnegative matrix factorization
Computers and Electrical Engineering
Detect and track latent factors with online nonnegative matrix factorization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Robust automatic data decomposition using a modified sparse NMF
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Spectral edit distance method for image clustering
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
A doubly weighted approach for appearance-based subspace learning methods
IEEE Transactions on Information Forensics and Security
Nonnegative matrix factorization with bounded total variational regularization for face recognition
Pattern Recognition Letters
IEEE Transactions on Neural Networks
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Correlated Noise: How it Breaks NMF, and What to Do About it
Journal of Signal Processing Systems
Class-specific discriminant non-negative matrix factorization for frontal face verification
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Two-dimensional non-negative matrix factorization for face representation and recognition
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
Fast non-negative dimensionality reduction for protein fold recognition
ECML'05 Proceedings of the 16th European conference on Machine Learning
Extended SMART algorithms for non-negative matrix factorization
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Non-monotone projection gradient method for non-negative matrix factorization
Computational Optimization and Applications
Multidimensional Systems and Signal Processing
Multistability of α-divergence based NMF algorithms
Computers & Mathematics with Applications
Correntropy-Based document clustering via nonnegative matrix factorization
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Solving non-negative matrix factorization by alternating least squares with a modified strategy
Data Mining and Knowledge Discovery
Modified subspace Barzilai-Borwein gradient method for non-negative matrix factorization
Computational Optimization and Applications
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Non-negative matrix factorization (NMF) technique has been recently proposed for dimensionality reduction. NMF is capable to produce region or part based representations of objects and images. Also, a direct modification of NMF, the weighted non-negative matrix factorization (WNMF) has also been introduced to improve the NMF capabilities of representing positive local data (as color histograms). A comparison between NMF, WNMF and the well-known principal component analysis (PCA) in the context of image patch classification has been carried out and it is claimed that all these three techniques can be combined in a common and unique classifier. This contribution is an extension of a previous study and we introduce the use of the WNMF as well as a probabilistic approach to compare all the three techniques noticing a great improvement in the final recognition results.