Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition without Correspondence using MultidimensionalReceptive Field Histograms
International Journal of Computer Vision
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-negative Matrix Factorization for Face Recognition
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Evaluation of distance metrics for recognition based on non-negative matrix factorization
Pattern Recognition Letters
Non-negative matrix factorization based methods for object recognition
Pattern Recognition Letters
Learning to Detect Objects in Images via a Sparse, Part-Based Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Orthogonal nonnegative matrix t-factorizations for clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Face recognition using localized features based on non-negative sparse coding
Machine Vision and Applications
Projected Gradient Methods for Nonnegative Matrix Factorization
Neural Computation
Low-Dimensional Polytope Approximation and Its Applications to Nonnegative Matrix Factorization
SIAM Journal on Scientific Computing
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Face Recognition Based on NMF and SVM
ISECS '09 Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01
A Penalty Function for Computing Orthogonal Non-negative Matrix Factorizations
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Wavelet transform methods for object detection and recovery
IEEE Transactions on Image Processing
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We study the problem of detecting and localizing objects in still, gray-scale images making use of the part-based representation provided by nonnegative matrix factorizations. Nonnegative matrix factorization represents an emerging example of subspace methods, which is able to extract interpretable parts from a set of template image objects and then to additively use them for describing individual objects. In this paper, we present a prototype system based on some nonnegative factorization algorithms, which differ in the additional properties added to the nonnegative representation of data, in order to investigate if any additional constraint produces better results in general object detection via nonnegative matrix factorizations.