On Photometric Issues in 3D Visual Recognition from aSingle 2D Image
International Journal of Computer Vision
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Incremental semi-supervised subspace learning for image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Learning an image manifold for retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Semantic manifold learning for image retrieval
Proceedings of the 13th annual ACM international conference on Multimedia
Non-negative tensor factorization with applications to statistics and computer vision
ICML '05 Proceedings of the 22nd international conference on Machine learning
Adaptive dimension reduction using discriminant analysis and K-means clustering
Proceedings of the 24th international conference on Machine learning
Knowledge and Information Systems
Learning a Maximum Margin Subspace for Image Retrieval
IEEE Transactions on Knowledge and Data Engineering
Computing non-negative tensor factorizations
Optimization Methods & Software - Mathematical programming in data mining and machine learning
Non-negative Matrix Factorization on Manifold
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Image retrieval using nonlinear manifold embedding
Neurocomputing
Tensor Decompositions and Applications
SIAM Review
Locality preserving nonnegative matrix factorization
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Local learning regularized nonnegative matrix factorization
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Discriminative sparse coding on multi-manifolds
Knowledge-Based Systems
| Hi-index | 0.01 |
Tensor provides a better representation for image space by avoiding information loss in vectorization. Nonnegative tensor factorization (NTF), whose objective is to express an n-way tensor as a sum of k rank-1 tensors under nonnegative constraints, has recently attracted a lot of attentions for its efficient and meaningful representation. However, NTF only sees Euclidean structures in data space and is not optimized for image representation as image space is believed to be a sub-manifold embedded in high-dimensional ambient space. To avoid the limitation of NTF, we propose a novel Laplacian regularized nonnegative tensor factorization (LRNTF) method for image representation and clustering in this paper. In LRNTF, the image space is represented as a 3-way tensor and we explicitly consider the manifold structure of the image space in factorization. That is, two data points that are close to each other in the intrinsic geometry of image space shall also be close to each other under the factorized basis. To evaluate the performance of LRNTF in image representation and clustering, we compare our algorithm with NMF, NTF, NCut and GNMF methods on three standard image databases. Experimental results demonstrate that LRNTF achieves better image clustering performance, while being more insensitive to noise.