Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Fixed-Point Algorithm and Maximum Likelihood Estimation forIndependent Component Analysis
Neural Processing Letters
Kernel Principal Component Analysis
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mercer Kernels for Object Recognition with Local Features
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Kernel Codebooks for Scene Categorization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering appearances of objects under varying illumination conditions
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Sequence-kernel based sparse representation for amateur video summarization
J-MRE '11 Proceedings of the 2011 joint ACM workshop on Modeling and representing events
Photo stream alignment for collaborative photo collection and sharing in social media
WSM '11 Proceedings of the 3rd ACM SIGMM international workshop on Social media
Scene classification using a multi-resolution bag-of-features model
Pattern Recognition
Sparse discriminative Fisher vectors in visual classification
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Face recognition via Weighted Sparse Representation
Journal of Visual Communication and Image Representation
Learning dictionary on manifolds for image classification
Pattern Recognition
Discriminative dictionary learning with pairwise constraints
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Design of non-linear discriminative dictionaries for image classification
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Learning to name faces: a multimodal learning scheme for search-based face annotation
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Kernel-based sparse representation for gesture recognition
Pattern Recognition
Semi-supervised learning with manifold fitted graphs
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Pose-based human action recognition via sparse representation in dissimilarity space
Journal of Visual Communication and Image Representation
Weighted discriminative sparsity preserving embedding for face recognition
Knowledge-Based Systems
Object Bank: An Object-Level Image Representation for High-Level Visual Recognition
International Journal of Computer Vision
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Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear similarity of features, which may reduce the feature quantization error and boost the sparse coding performance, we propose Kernel Sparse Representation(KSR). KSR is essentially the sparse coding technique in a high dimensional feature space mapped by implicit mapping function. We apply KSR to both image classification and face recognition. By incorporating KSR into Spatial Pyramid Matching(SPM), we propose KSRSPM for image classification. KSRSPM can further reduce the information loss in feature quantization step compared with Spatial Pyramid Matching using Sparse Coding(ScSPM). KSRSPM can be both regarded as the generalization of Efficient Match Kernel(EMK) and an extension of ScSPM. Compared with sparse coding, KSR can learn more discriminative sparse codes for face recognition. Extensive experimental results show that KSR outperforms sparse coding and EMK, and achieves state-of-the-art performance for image classification and face recognition on publicly available datasets.