CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Local Non-Negative Matrix Factorization as a Visual Representation
ICDL '02 Proceedings of the 2nd International Conference on Development and Learning
Document clustering by concept factorization
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Robust Fragments-based Tracking using the Integral Histogram
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
ACM Computing Surveys (CSUR)
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental subspace learning via non-negative matrix factorization
Pattern Recognition
Non-negative Matrix Factorization on Manifold
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Toward Faster Nonnegative Matrix Factorization: A New Algorithm and Comparisons
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Detect and track latent factors with online nonnegative matrix factorization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Linear and nonlinear projective nonnegative matrix factorization
IEEE Transactions on Neural Networks
Incremental MPCA for Color Object Tracking
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Recent advances and trends in visual tracking: A review
Neurocomputing
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks
Non-Negative Patch Alignment Framework
IEEE Transactions on Neural Networks
Visual tracking via adaptive structural local sparse appearance model
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Robust object tracking via sparsity-based collaborative model
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
A convergent algorithm for orthogonal nonnegative matrix factorization
Journal of Computational and Applied Mathematics
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This paper presents a novel incremental orthogonal projective non-negative matrix factorization (IOPNMF) algorithm, which is aimed to learn a parts-based subspace that reveals dynamic data streams. By assuming that the newly added samples only affect basis vectors but do not affect the coefficients of old samples, we propose an objective function for on-line learning and then present a multiplicative update rule to solve it. Compared with other non-negative matrix factorization (NMF) methods, our algorithm can guarantee to learn a linear parts-based subspace in an on-line fashion, which may facilitate some real applications. The facial analysis experiment shows that our IOPNMF method learns parts-based components successfully. In addition, we present an effective tracking method by integrating the IOPNMF method, the idea of sparse representation and the domain information of object tracking. The proposed tracker explicitly takes partial occlusion and mis-alignment into account for appearance model update and object tracking. The experimental results on some challenging image sequences demonstrate the proposed tracking algorithm performs favorably against several state-of-the-art methods.