Jolliffe, I.T.,
Principal Component Analysis,
Springer-VerlagNew-York, 1986.
Survey, PCA. The Book, overview.
BibRef
8600
Shimura, M.[Masamichi],
Imai, T.[Toshio],
Nonsupervised classification using the principal component,
PR(5), No. 4, December 1973, pp. 353-363.
WWW Version.
0309
BibRef
Wold, S.[Svante],
Pattern recognition by means of disjoint principal components models,
PR(8), No. 3, July 1976, pp. 127-139.
WWW Version.
0309
BibRef
Chang, C.C.,
Chen, Y.W.,
Buehrer, D.J.,
A Two-Dimensional Shape Recognition Scheme Based on
Principal Component Analysis,
PRAI(8), 1994, pp. 859-875.
BibRef
9400
Chen, C.Y.,
Chang, C.C., and
Lee, R.C.T.,
A Near Pattern-Matching Scheme Based upon Principal Component Analysis,
PRL(16), 1995, pp. 339-345.
See also Exact Match Retrieval Scheme Based Upon Principal Component Analysis, An.
BibRef
9500
Chang, C.I.[C. I],
Du, Q.,
Interference and Noise-Adjusted Principal Components Analysis,
GeoRS(37), No. 5, September 1999, pp. 2387.
IEEE Top Reference.
BibRef
9909
Weingessel, A.[Andreas],
Bischof, H.[Horst],
Hornik, K.[Kurt],
Leisch, F.[Friedrich],
Adaptive Combination of PCA and VQ Networks,
TNN(8), No. 5, 1997, pp. 1208-1211.
BibRef
9700
Earlier:
Hierarchies of Autoassociators,
ICPR96(IV: 200-204).
WWW Version.
9608(Technical Univ. of Vienna, A)
BibRef
Crowley, J.L.,
Pourraz, F.,
Continuity properties of the appearance manifold for mobile robot
position estimation,
IVC(19), No. 11, September 2001, pp. 741-752.
WWW Version. PCA. Orthogonal basis to represent appearance from different positions.
0108
BibRef
Twining, C.J.,
Taylor, C.J.,
The use of kernel principal component analysis to model data
distributions,
PR(36), No. 1, January 2003, pp. 217-227.
WWW Version.
0210
BibRef
Glendinning, R.H.,
Herbert, R.A.,
Shape classification using smooth principal components,
PRL(24), No. 12, August 2003, pp. 2021-2030.
WWW Version.
0304
BibRef
de la Torre, F.[Fernando],
Black, M.J.[Michael J.],
Robust Parameterized Component Analysis:
Theory and Applications to 2D Facial Appearance Models,
CVIU(91), No. 1-2, July-August 2003, pp. 53-71.
WWW Version.
PDF Version.
0309
BibRef
Earlier:
Robust Parameterized Component Analysis,
ECCV02(IV: 653 ff.).
HTML Version.
0205
BibRef
Earlier:
Robust Principal Component Analysis for Computer vision,
ICCV01(I: 362-369).
WWW Version.
0106
BibRef
And:
Dynamic Coupled Component Analysis,
CVPR01(II:643-650).
IEEE Abstract. IEEE Top Reference.
0110
BibRef
de la Torre, F.,
Kanade, T.,
Oriented Discriminant Analysis,
BMVC04(xx-yy).
HTML Version.
0508
BibRef
Sengel, M.,
Bischof, H.,
Efficient representation of in-plane rotation within a PCA framework,
IVC(23), No. 12, 1 November 2005, pp. 1051-1059.
WWW Version.
0510
BibRef
Vidal, R.,
Ma, Y.[Yi],
Sastry, S.,
Generalized Principal Component Analysis (GPCA),
PAMI(27), No. 12, December 2005, pp. 1945-1959.
WWW Version.
0512
BibRef
Earlier:
CVPR03(I: 621-628).
IEEE Abstract. IEEE Top Reference.
0307
BibRef
Vidal, R.,
Ma, Y.[Yi],
Piazzi, J.,
A new GPCA algorithm for clustering subspaces by fitting,
differentiating and dividing polynomials,
CVPR04(I: 510-517).
IEEE Abstract. IEEE Top Reference.
0408
BibRef
Nagabhushan, P.,
Guru, D.S.,
Shekar, B.H.,
Visual learning and recognition of 3D objects using two-dimensional
principal component analysis: A robust and an efficient approach,
PR(39), No. 4, April 2006, pp. 721-725.
WWW Version. Principal component analysis; Appearance based model; Object recognition
0604
BibRef
Earlier: A3, A2, A1:
Object Recognition Through the Principal Component Analysis of Spatial
Relationship Amongst Lines,
ACCV06(I:170-179).
WWW Version.
0601
BibRef
Shekar, B.H.,
Guru, D.S.,
Nagabhushan, P.,
Two-Dimensional Optimal Transform for Appearance Based Object
Recognition,
ICCVGIP06(650-661).
WWW Version.
0612
BibRef
Irpino, A.[Antonio],
'Spaghetti' PCA analysis: An extension of principal components analysis
to time dependent interval data,
PRL(27), No. 5, 1 April 2006, pp. 504-513.
WWW Version.
0604Interval data; Time dependent; Oriented intervals
BibRef
Sharma, A.[Alok],
Paliwal, K.K.[Kuldip K.],
Onwubolu, G.C.[Godfrey C.],
Class-dependent PCA, MDC and LDA:
A combined classifier for pattern classification,
PR(39), No. 7, July 2006, pp. 1215-1229.
WWW Version.
0606Classification accuracy; Total parameter requirement; Processing time;
Class-dependent PCA; LDA
BibRef
Sharma, A.[Alok],
Paliwal, K.K.[Kuldip K.],
Subspace independent component analysis using vector kurtosis,
PR(39), No. 11, November 2006, pp. 2227-2232.
WWW Version.
0608Blind source separation; Subspace ICA; Vector kurtosis
BibRef
Sharma, A.[Alok],
Paliwal, K.K.[Kuldip K.],
Fast principal component analysis using fixed-point algorithm,
PRL(28), No. 10, 15 July 2007, pp. 1151-1155.
WWW Version.
0706Fast PCA; Eigenvalue decomposition; Mean squared error
BibRef
Vaswani, N.,
Chellappa, R.,
Principal Components Null Space Analysis for Image and Video
Classification,
IP(15), No. 7, July 2006, pp. 1816-1830.
WWW Version.
0606
BibRef
Earlier:
Classification probability analysis of principal component null space
analysis,
ICPR04(I: 240-243).
WWW Version.
0409
BibRef
Wu, F.C.,
Hu, Z.Y.,
The LLE and a linear mapping,
PR(39), No. 9, September 2006, pp. 1799-1804.
WWW Version.
0606Locally linear embedding (LLE); Linear mapping;
Principal component analysis
BibRef
Tao, Q.[Qing],
Wu, G.W.[Gao-Wei],
Wang, J.[Jue],
Learning linear PCA with convex semi-definite programming,
PR(40), No. 10, October 2007, pp. 2633-2640.
WWW Version.
0707Principal component analysis; Statistical learning theory;
Support vector machines; Margin; Maximal margin algorithm;
Semi-definite programming; Robustness
BibRef
Tzimiropoulos, G.,
Mitianoudis, N.,
Stathaki, T.,
Robust Recognition of Planar Shapes Under Affine Transforms Using
Principal Component Analysis,
SPLetters(14), No. 10, October 2007, pp. 723-726.
WWW Version.
0711
BibRef
Kumar, K.V.[Kadappagari Vijaya],
Negi, A.[Atul],
SubXPCA and a generalized feature partitioning approach to principal
component analysis,
PR(41), No. 4, April 2008, pp. 1398-1409.
WWW Version.
0801Dimensionality reduction; Principal component analysis;
Sub-pattern based PCA; Feature partitioning
BibRef
Kumar, K.V.[Kadappagari Vijaya],
Negi, A.[Atul],
Novel approaches to principal component analysis of image data based on
feature partitioning framework,
PRL(29), No. 3, 1 February 2008, pp. 254-264.
WWW Version.
0801Dimensionality reduction; PCA; Image principal component analysis;
Feature partitioning; Face recognition
BibRef
Maret, Y.,
Nikolopoulos, S.,
Dufaux, F.,
Ebrahimi, T.,
Nikolaidis, N.,
A Novel Replica Detection System using Binary Classifiers, R-Trees, and
PCA,
ICIP06(925-928).
0610
WWW Version.
BibRef
Sarkis, M.,
Dawy, Z.,
Obermeier, F.,
Diepold, K.,
Automatic Model-Order Selection for PCA,
ICIP06(933-936).
0610
WWW Version.
BibRef
Lu, H.[Haiping],
Plataniotis, K.N.,
Venetsanopoulos, A.N.,
Multilinear Principal Component Analysis of Tensor Objects for
Recognition,
ICPR06(II: 776-779).
WWW Version.
0609
BibRef
Rathi, Y.[Yogesh],
Dambreville, S.[Samuel],
Tannenbaum, A.[Allen],
Comparative Analysis of Kernel Methods for Statistical Shape Learning,
CVAMIA06(96-107).
WWW Version.
0605
BibRef
Dambreville, S.[Samuel],
Rathi, Y.[Yogesh],
Tannenbaum, A.[Allen],
Shape-Based Approach to Robust Image Segmentation using Kernel PCA,
CVPR06(I: 977-984).
WWW Version.
0606
BibRef
And:
A Shape-Based Approach to Robust Image Segmentation,
ICIAR06(I: 173-183).
WWW Version.
0610
BibRef
Jin, Z.[Zhong],
Davoine, F.[Franck],
Lou, Z.[Zhen],
Yang, J.Y.[Jing-Yu],
A Novel PCA-Based Bayes Classifier and Face Analysis,
ICB06(144-150).
WWW Version.
0601
BibRef
Hosic, S.[Sabina],
Hocanin, A.[Aykut],
Demirel, H.[Hasan],
Unequal Error Protection Using Convolutional Codes for PCA-Coded Images,
ICIAR05(335-342).
WWW Version.
0509
BibRef
Jin, Z.[Zhong],
Davoine, F.[Franck],
Orthogonal ICA representation of images,
ICARCV04(I: 369-374).
WWW Version.
0412
BibRef
Tanaka, T.,
Generalized subspace rules for on-line PCA and their application in
signal and image compression,
ICIP04(III: 1895-1898).
WWW Version.
0505
BibRef
Romaniuk, B.,
Guilloux, V.,
Desvignes, M.,
Deshayes, M.J.,
Partially observed objects localization with PCA and KPCA models,
Southwest04(80-84).
IEEE Abstract. IEEE Top Reference.
0411
BibRef
Ke, Y.[Yan],
Sukthankar, R.,
PCA-SIFT: a more distinctive representation for local image descriptors,
CVPR04(II: 506-513).
IEEE Abstract. IEEE Top Reference.
0408
See also Distinctive Image Features from Scale-Invariant Keypoints.
BibRef
Meltzer, J.[Jason],
Yang, M.H.[Ming-Hsuan],
Gupta, R.[Rakesh],
Soatto, S.[Stefano],
Multiple View Feature Descriptors from Image Sequences via Kernel
Principal Component Analysis,
ECCV04(Vol I: 215-227).
WWW Version.
0405
BibRef
Le Bihan, N.,
Sangwine, S.J.,
Quaternion principal component analysis of color images,
ICIP03(I: 809-812).
IEEE Abstract. IEEE Top Reference.
0312
BibRef
Zeng, X.Y.[Xiang-Yan],
Chen, Y.W.[Yen-Wei],
Nakao, Z.,
Image feature representation by the subspace of nonlinear PCA,
ICPR02(II: 228-231).
WWW Version.
0211
BibRef
Hegazy, D.[Doaa],
Denzler, J.[Joachim],
Generic Object Recognition Using Boosted Combined Features,
RobVis08(355-366).
WWW Version.
0802
BibRef
Drexler, C.,
Mattern, F.,
Denzler, J.,
Appearance Based Generic Object Modeling and Recognition Using
Probabilistic Principal Component Analysis,
DAGM02(100 ff.).
HTML Version.
0303
BibRef
Perantonis, S.J.,
Petridis, S.,
Virvilis, V.,
Supervised Principal Component Analysis Using a Smooth Classifier
Paradigm,
ICPR00(Vol II: 109-112).
WWW Version.
HTML Version.
0009
BibRef
Surendro, K.[Kridanto],
Anzai, Y.[Yuichiro],
Non-rigid object recognition using principal component analysis and
geometric hashing,
CAIP97(50-57).
WWW Version.
9709
BibRef
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Invariants -- Independent Component Analysis .