13.4.1.2 Other, Kernel Methods, Invariants

Chapter Contents (Back)
Kernel Methods. Object Recognition.
See also Other Sparse Coding, Low Dimensional Representation, Invariants.

Nasios, N.[Nikolaos], Bors, A.G.[Adrian G.],
Kernel-based classification using quantum mechanics,
PR(40), No. 3, March 2007, pp. 875-889.
Elsevier DOI 0611
Kernel density estimation; Nonparametric modelling; Quantum mechanics; Vector field segmentation BibRef

Subrahmanya, N.[Niranjan], Shin, Y.C.[Yung C.],
Sparse Multiple Kernel Learning for Signal Processing Applications,
PAMI(32), No. 5, May 2010, pp. 788-798.
IEEE DOI 1003
For nonlinear models. BibRef

Pan, B.B.[Bin-Bin], Lai, J.H.[Jian-Huang], Chen, W.S.[Wen-Sheng],
Nonlinear nonnegative matrix factorization based on Mercer kernel construction,
PR(44), No. 10-11, October-November 2011, pp. 2800-2810.
Elsevier DOI 1101
Nonnegative matrix factorization; Mercer kernel; Kernel mapping; Face recognition BibRef

Chen, W.S.[Wen-Sheng], Li, Y.G.[Yu-Gao], Pan, B.B.[Bin-Bin], Chen, B.[Bo],
Incremental learning based on block sparse kernel nonnegative matrix factorization,
ICWAPR16(219-224)
IEEE DOI 1611
Databases BibRef

Mantrach, A.[Amin], van Zeebroeck, N.[Nicolas], Francq, P.[Pascal], Shimbo, M.[Masashi], Bersini, H.[Hugues], Saerens, M.[Marco],
Semi-supervised classification and betweenness computation on large, sparse, directed graphs,
PR(44), No. 6, June 2011, pp. 1212-1224.
Elsevier DOI 1102
Graph mining; Semi-supervised classification; Within-network classification; Betweenness centrality; Graph-based classification; Kernel methods; Kernel on a graph; Large-scale graphs BibRef

Ohkawa, Y.[Yasuhiro], Fukui, K.[Kazuhiro],
Hand-Shape Recognition Using the Distributions of Multi-Viewpoint Image Sets,
IEICE(E95-D), No. 6, June 2012, pp. 1619-1627.
WWW Link. 1206
BibRef

Ohkawa, Y.[Yasuhiro], Suryanto, C.H.[Chendra Hadi], Fukui, K.[Kazuhiro],
Image Set-Based Hand Shape Recognition Using Camera Selection Driven by Multi-class AdaBoosting,
ISVC11(II: 555-566).
Springer DOI 1109
BibRef
Earlier: A1, A3, Only:
Hand Shape Recognition Based on Kernel Orthogonal Mutual Subspace Method,
MVA09(122-).
PDF File. 0905
BibRef

Fukui, K.[Kazuhiro], Stenger, B.[Björn], Yamaguchi, O.[Osamu],
A Framework for 3D Object Recognition Using the Kernel Constrained Mutual Subspace Method,
ACCV06(II:315-324).
Springer DOI 0601
map input into feature space. Project onto kernel subspace. BibRef

Fukui, K.[Kazuhiro], Yamaguchi, O.[Osamu],
The Kernel Orthogonal Mutual Subspace Method and Its Application to 3D Object Recognition,
ACCV07(II: 467-476).
Springer DOI 0711
BibRef
Earlier: A2, A1:
Pattern hashing: Object recognition based on a distributed local appearance model,
ICIP02(III: 329-332).
IEEE DOI 0210
BibRef

Igarashi, Y.[Yosuke], Fukui, K.[Kazuhiro],
3D Object Recognition Based on Canonical Angles between Shape Subspaces,
ACCV10(IV: 580-591).
Springer DOI 1011
BibRef

Akihiro, N.[Naoki], Fukui, K.[Kazuhiro],
Compound Mutual Subspace Method for 3D Object Recognition: A Theoretical Extension of Mutual Subspace Method,
Subspace10(374-383).
Springer DOI 1109
BibRef

Liao, C.T.[Chia-Te], Lai, S.H.[Shang-Hong],
Robust kernel-based learning for image-related problems,
IET-IPR(6), No. 6, 2012, pp. 795-803.
DOI Link 1210
BibRef
Earlier:
A novel robust kernel for appearance-based learning,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kuang, J.J.[Jin-Jun], Chai, Y.[Yi],
Robust Scene Categorization via Scale-Rotation Invariant Generative Model and Kernel Sparse Representation Classification,
IEICE(E96-D), No. 3, March 2013, pp. 758-761.
WWW Link. 1303
BibRef

Sun, T.[Tao], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Wang, S.[Shuang], Feng, J.[Jie],
Selective multiple kernel learning for classification with ensemble strategy,
PR(46), No. 11, November 2013, pp. 3081-3090.
Elsevier DOI 1306
Ensemble learning; Kernel evaluation; Multiple kernel learning; Selective multiple kernel learning; Fast selective multiple kernel learning BibRef

Guo, L.H.[Li-Hua],
Locality-Constrained Multi-Task Joint Sparse Representation for Image Classification,
IEICE(E96-D), No. 9, September 2013, pp. 2177-2181.
WWW Link. 1309
BibRef

Guo, L.H.[Li-Hua],
From Easy to Difficult: A Self-Paced Multi-Task Joint Sparse Representation Method,
IEICE(E101-D), No. 8, August 2018, pp. 2115-2122.
WWW Link. 1808
BibRef

Guo, L.H.[Li-Hua],
Manifold Kernel Metric Learning for Larger-Scale Image Annotation,
IEICE(E98-D), No. 7, July 2015, pp. 1396-1400.
WWW Link. 1508
BibRef

Lampert, C.H.[Christoph H.],
Kernel Methods in Computer Vision,
FTCGV(4), Issue 3, 2008, pp. 193-285.
DOI Link 1410
Published September 2009. BibRef

Liu, W.Y.[Wei-Yang], Yu, Z.D.[Zhi-Ding], Lu, L.J.[Li-Jia], Wen, Y.D.[Yan-Dong], Li, H.[Hui], Zou, Y.X.[Yue-Xian],
KCRC-LCD: Discriminative kernel collaborative representation with locality constrained dictionary for visual categorization,
PR(48), No. 10, 2015, pp. 3076-3092.
Elsevier DOI 1507
Kernel collaborative representation BibRef

Liu, W.Y.[Wei-Yang], Yu, Z.D.[Zhi-Ding], Wen, Y.D.[Yan-Dong], Lin, R.M.[Rong-Mei], Yang, M.[Meng],
Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Liu, W.Y.[Wei-Yang], Yu, Z.D.[Zhi-Ding], Wen, Y.D.[Yan-Dong], Yang, M.[Meng], Zou, Y.X.[Yue-Xian],
Multi-kernel collaborative representation for image classification,
ICIP15(21-25)
IEEE DOI 1512
Collaborative Representation; Image Classification; Multi-Kernel BibRef

Liu, W.Y.[Wei-Yang], Lu, L.[Lijia], Li, H.[Hui], Wang, W.[Wei], Zou, Y.X.[Yue-Xian],
A novel kernel collaborative representation approach for image classification,
ICIP14(4241-4245)
IEEE DOI 1502
Accuracy BibRef

Li, X.[Xiao], Fang, M.[Min], Wang, H.C.[Hong-Chun], Zhang, J.J.[Ju-Jie],
Supervised transfer kernel sparse coding for image classification,
PRL(68, Part 1), No. 1, 2015, pp. 27-33.
Elsevier DOI 1512
Transfer learning BibRef

Li, X.[Xiao], Fang, M.[Min], Zhang, J.J.[Ju-Jie], Wu, J.Q.[Jin-Qiao],
Sample selection for visual domain adaptation via sparse coding,
SP:IC(44), No. 1, 2016, pp. 92-100.
Elsevier DOI 1605
Image classification BibRef

Cinbis, R.G.[Ramazan Gokberk], Verbeek, J.[Jakob], Schmid, C.[Cordelia],
Approximate Fisher Kernels of Non-iid Image Models for Image Categorization,
PAMI(38), No. 6, June 2016, pp. 1084-1098.
IEEE DOI 1605
BibRef
Earlier:
Image categorization using Fisher kernels of non-iid image models,
CVPR12(2184-2191).
IEEE DOI 1208
Analytical models BibRef

Marukatat, S.[Sanparith],
Kernel matrix decomposition via empirical kernel map,
PRL(77), No. 1, 2016, pp. 50-57.
Elsevier DOI 1606
Kernel PCA BibRef

Ji, R.R.[Rong-Rong], Cao, L.J.[Liu-Juan], Wang, Y.[Yan],
Joint Depth and Semantic Inference from a Single Image via Elastic Conditional Random Field,
PR(59), No. 1, 2016, pp. 268-281.
Elsevier DOI 1609
Depth estimation BibRef

Wang, Y.[Yan], Ji, R.R.[Rong-Rong], Chang, S.F.[Shih-Fu],
Label Propagation from ImageNet to 3D Point Clouds,
CVPR13(3135-3142)
IEEE DOI 1309
BibRef

Liu, W.[Wei], Wang, J.[Jun], Ji, R.R.[Rong-Rong], Jiang, Y.G.[Yu-Gang], Chang, S.F.[Shih-Fu],
Supervised hashing with kernels,
CVPR12(2074-2081).
IEEE DOI 1208
BibRef

Zhang, G., Sun, H., Xia, G., Sun, Q.,
Multiple Kernel Sparse Representation-Based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension,
IP(25), No. 9, September 2016, pp. 4271-4285.
IEEE DOI 1609
image classification BibRef

Wang, B.[Bo], Guo, J.C.[Ji-Chang], Zhang, Y.[Yan], Li, C.Y.[Chong-Yi],
Hierarchical feature concatenation-based kernel sparse representations for image categorization,
VC(33), No. 5, May 2017, pp. 647-663.
Springer DOI 1704
BibRef

Ahn, S.G.[Seon-Gin], Ryu, D.W.[Dong-Woo], Lee, S.H.[Sang-Ho],
A Machine Learning-Based Approach for Spatial Estimation Using the Spatial Features of Coordinate Information,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link 2010
BibRef


Souilem, N., Elaissi, I., Taouali, O., Hassani, M.,
Identification of non linear system modeled in Reproducing Kernel Hilbert Space using a new criterion,
ICCVIA15(1-6)
IEEE DOI 1603
BibRef
And: ICCVIA15(1-6)
IEEE DOI 1603
Hilbert spaces Biological system modeling BibRef

Shen, B.[Bin], Xu, Z.L.[Zeng-Lin], Allebach, J.P.[Jan P.],
Kernel tapering: A simple and effective approach to sparse kernels for image processing,
ICIP14(4917-4921)
IEEE DOI 1502
Accuracy BibRef

Hartley, R.I.[Richard I.],
Keynote lecture 2: 'Riemannian manifolds, kernels and learning',
AVSS14(XV-XV)
IEEE DOI 1411
Computational modeling BibRef

Aljundi, R.[Rahaf], Emonet, R.[Remi], Muselet, D.[Damien], Sebban, M.[Marc],
Landmarks-based kernelized subspace alignment for unsupervised domain adaptation,
CVPR15(56-63)
IEEE DOI 1510
BibRef

Fernando, B.[Basura], Habrard, A.[Amaury], Sebban, M.[Marc], Tuytelaars, T.[Tinne],
Unsupervised Visual Domain Adaptation Using Subspace Alignment,
ICCV13(2960-2967)
IEEE DOI 1403
domain adaptation; object recognition; subspace alignment Map one subspace to the other. BibRef

Li, P.H.[Pei-Hua], Wang, Q.L.[Qi-Long], Zuo, W.M.[Wang-Meng], Zhang, L.[Lei],
Log-Euclidean Kernels for Sparse Representation and Dictionary Learning,
ICCV13(1601-1608)
IEEE DOI 1403
Dictionary Learning BibRef

Xie, B.[Bojun], Liu, Y.[Yi], Zhang, H.[Hui], Yu, J.[Jian],
Efficient kernel descriptor for image categorization via pivots selection,
ICIP13(3479-3483)
IEEE DOI 1402
Efficient kernel descriptor BibRef

Pan, B.B.[Bin-Bin], Chen, W.S.[Wen-Sheng],
Learning Geometry-Aware Kernels in a Regularization Framework,
CAIP13(352-359).
Springer DOI 1308
BibRef

Wang, B.T.[Bo-Tao], Xiong, H.K.[Hong-Kai], Jiang, X.Q.[Xiao-Qian], Ling, F.[Fan],
Semi-supervised object recognition using structure kernel,
ICIP12(2157-2160).
IEEE DOI 1302
BibRef

Antanas, L.[Laura], Hoffmann, M., Frasconi, P.[Paolo], Tuytelaars, T.[Tinne], de Raedt, L.[Luc],
A relational kernel-based approach to scene classification,
WACV13(133-139).
IEEE DOI 1303
BibRef

Antanas, L.[Laura], Frasconi, P.[Paolo], Costa, F.[Fabrizio], Tuytelaars, T.[Tinne], de Raedt, L.[Luc],
A Relational Kernel-Based Framework for Hierarchical Image Understanding,
SSSPR12(171-180).
Springer DOI 1211
BibRef

Poczos, B.[Barnabas], Xiong, L.[Liang], Sutherland, D.J.[Dougal J.], Schneider, J.[Jeff],
Nonparametric kernel estimators for image classification,
CVPR12(2989-2996).
IEEE DOI 1208
BibRef

Gavves, E.[Efstratios], Snoek, C.G.M.[Cees G.M.], Smeulders, A.W.M.[Arnold W.M.],
Convex reduction of high-dimensional kernels for visual classification,
CVPR12(3610-3617).
IEEE DOI 1208
BibRef

Zhang, N.[Ning], Farrell, R.[Ryan], Darrell, T.J.[Trever J.],
Pose pooling kernels for sub-category recognition,
CVPR12(3665-3672).
IEEE DOI 1208
BibRef

Li, H.X.[Han-Xi], Gao, Y.S.[Yong-Sheng], Sun, J.[Jun],
Fast Kernel Sparse Representation,
DICTA11(72-77).
IEEE DOI 1205
BibRef

Sakano, H.[Hitoshi], Yamaguchi, O.[Osamu], Kawahara, T.[Tomokazu], Hotta, S.[Seiji],
On the Behavior of Kernel Mutual Subspace Method,
Subspace10(364-373).
Springer DOI 1109
BibRef

Le, T.T.[Tam T.], Kang, Y.[Yousun], Sugimoto, A.[Akihiro], Tran, S.T.[Son T.], Nguyen, T.D.[Thuc D.],
Hierarchical Spatial Matching Kernel for Image Categorization,
ICIAR11(I: 141-151).
Springer DOI 1106
BibRef

Bo, L.F.[Lie-Feng], Lai, K.[Kevin], Ren, X.F.[Xiao-Feng], Fox, D.[Dieter],
Object recognition with hierarchical kernel descriptors,
CVPR11(1729-1736).
IEEE DOI 1106
Kernel descriptors turn pixels into patch features, then with SVM. BibRef

Huang, D.[Dong], Tian, Y.D.[Yuan-Dong], de la Torre, F.[Fernando],
Local isomorphism to solve the pre-image problem in kernel methods,
CVPR11(2761-2768).
IEEE DOI 1106
BibRef

Mukherjee, L.[Lopamudra], Peng, J.M.[Ji-Ming], Sigmund, T.[Trevor], Singh, V.[Vikas],
Network Flow Formulations for Learning Binary Hashing,
ECCV16(V: 366-381).
Springer DOI 1611
BibRef

Mukherjee, L.[Lopamudra], Singh, V.[Vikas], Peng, J.M.[Ji-Ming], Hinrichs, C.[Chris],
Learning kernels for variants of normalized cuts: Convex relaxations and applications,
CVPR10(3145-3152).
IEEE DOI 1006
BibRef

Zeng, Z.[Zhi], Li, H.P.[He-Ping], Liang, W.[Wei], Zhang, S.W.[Shu-Wu],
Similarity-based image classification via kernelized sparse representation,
ICIP10(277-280).
IEEE DOI 1009
BibRef

Li, F.X.[Fu-Xin], Ionescu, C.[Catalin], Sminchisescu, C.[Cristian],
Random Fourier Approximations for Skewed Multiplicative Histogram Kernels,
DAGM10(262-271).
Springer DOI 1009
Award, GCPR, HM. BibRef

Yakhnenko, O.[Oksana], Honavar, V.[Vasant],
Multiple label prediction for image annotation with multiple Kernel correlation models,
VCL-ViSU09(8-15).
IEEE DOI 0906
To correlate text keywords with image. Uses captions.
See also Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope. BibRef

Haasdonk, B., Vossen, A., Burkhardt, H.,
Invariance in Kernel Methods by Haar-Integration Kernels,
SCIA05(841-851).
Springer DOI 0506
BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Active Appearance Models: AAM .


Last update:Mar 16, 2024 at 20:36:19