14.3 Robust Techniques, Robust Classification

Chapter Contents (Back)
Robust Technique. Robust techniques are characterized by the number of errors tolerated. A level of 0% means that single errors in the input data cause errors in the output. 50% would correspond to least median of squares -- half of the data may be bad.

Huber, P.J.,
Robust Statistics,
John Wiley&Sons, New York, 1981. The place to start to know what it all means. BibRef 8100

Rousseeuw, P.J.,
Robust Regression and Outlier Detection,
John Wiley&Sons, New York, 1987. BibRef 8700

Rousseeuw, P.J.,
Least Median of Squares Regression,
ASAJ(79), 1984, pp. 871-880. BibRef 8400

Besl, P.J., Birch, J.B., Watson, L.T.,
Robust Window Operators,
MVA(2), 1989, pp. 179-191. BibRef 8900
Earlier: ICCV88(591-600).
IEEE DOI BibRef

Gupta, L.[Lalit], Sayeh, M.R.[Mohammad R.], Tammana, R.[Ravi],
A Neural Network Approach to Robust Shape Classification,
PR(23), No. 6, 1990, pp. 563-568.
WWW Link. 3 layer net. BibRef 9000

Gutfinger, D., Sklansky, J.,
Robust classifiers by mixed adaptation,
PAMI(13), No. 6, June 1991, pp. 552-567.
IEEE DOI BibRef 9106

Zhuang, X., Wang, T., and Zhang, P.,
A Highly Robust Estimator through Partially Likelihood Function Modeling and Its Application in Computer Vision,
PAMI(14), No. 1, January 1992, pp. 19-35.
IEEE DOI BibRef 9201

Zhuang, X., and Zhang, P.,
A Highly Robust Estimator for Computer Vision,
ICPR90(I: 545-550).
IEEE DOI BibRef 9000

Hampshire, II, J.B., and Waibel, A.,
The Meta-Pi Network: Building Distributed Knowledge Representations for Robust Multisource Pattern Recognition,
PAMI(14), No. 7, July 1992, pp. 751-769.
IEEE DOI BibRef 9207

Meer, P.[Peter], Mintz, D.[Doron], Kim, D.Y.[Dong Yoon], Rosenfeld, A.[Azriel],
Robust Regression Methods for Computer Vision: A Review,
IJCV(6), No. 1, April 1991, pp. 59-70.
Springer DOI BibRef 9104

Mintz, D., Meer, P., and Rosenfeld, A.,
Consensus by Decomposition: A Paradigm for Fast High Breakdown Point Robust Estimation,
DARPA92(345-362). More on the topic. BibRef 9200

Meer, P.[Peter],
Robust High Breakdown Estimation and Consensus,
AMV Strategies921992, pp. 23-33. See See also Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. BibRef 9200

Meer, P., Mintz, D., and Rosenfeld, A.,
Analysis of the Least median of Squares Estimator for Computer Vision Applications,
CVPR92(621-623).
IEEE DOI BibRef 9200
Earlier:
Least Median of Squares Based Robust Analysis of Image Structure,
DARPA90(231-254). Least Median. They also have papers in the Robust Vision Workshop on similar topics. See also Robust Consensus Based Edge-Detection. BibRef

Meer, P., Mintz, D., and Rosenfeld, A.,
Robust Recovery of Precursive Polynomial Image Structure,
Robust90(xx). BibRef 9000

Kim, D.Y., Kim, J.J., Meer, P., Mintz, D., Rosenfeld, A.,
Robust Computer Vision: A Least Median of Squares Based Approach,
DARPA89(1117-1134). BibRef 8900

Mintz, D., Meer, P., and Rosenfeld, A.,
A Fast, High Breakdown Point Robust Estimator for Computer Vision Applications,
DARPA90(255-257). BibRef 9000

Mintz, D.,
Robustness by Consensus,
UMD-CAR-TR-576. 1991. BibRef 9100

Urahama, K., Furukawa, Y.,
Gradient descent learning of nearest neighbor classifiers with outlier rejection,
PR(28), No. 5, May 1995, pp. 761-768.
WWW Link. 0401
BibRef

Olson, C.F.[Clark F.],
An Approximation Algorithm for Least Median of Squares Regression,
IPL(63), No. 5, September 1997, 237-241.
WWW Link. BibRef 9709

Li, S.Z.,
Discontinuous MRF Prior and Robust Statistics: A Comparative-Study,
IVC(13), No. 3, April 1995, pp. 227-233.
WWW Link. BibRef 9504

Mount, D.M., Netanyahu, N.S.,
Computationally Efficient Algorithms for High-Dimensional Robust Estimators,
GMIP(56), No. 4, July 1994, pp. 289-303. BibRef 9407

Ney, H.[Hermann], Essen, U.[Ute], Kneser, R.[Reinhard],
On the Estimation of 'Small' Probabilities by Leaving-One-Out,
PAMI(17), No. 12, December 1995, pp. 1202-1212.
IEEE DOI Training samples are less than the number of possible classes. BibRef 9512

Brunelli, R., Messelodi, S.,
Robust Estimation Of Correlation With Applications To Computer Vision,
PR(28), No. 6, June 1995, pp. 833-841.
WWW Link. BibRef 9506

Black, M.J., Rangarajan, A.,
On The Unification of Line Processes, Outlier Rejection, and Robust Statistics with Applications in Early Vision,
IJCV(19), No. 1, July 1996, pp. 57-91.
Springer DOI
PDF File. 9608
BibRef
Earlier:
The Outlier Process: Unifying Line Processes and Robust Statistics,
CVPR94(15-22).
IEEE DOI Applied to reconstruction of degraded images. BibRef

Zhou, P., Pycock, D.,
Robust Statistical-Models for Cell Image Interpretation,
IVC(15), No. 4, April 1997, pp. 307-316.
WWW Link. 9706
BibRef
Earlier:
Robust Statistical Model-Based Cell Image Interpretation,
BMVC95(xx-yy).
PDF File. 9509
BibRef
And:
Robust Model-Based Boundary Cue Generation for Cell Image Interpretation,
BMVC95(xx-yy).
PDF File. 9509
BibRef

Bosdogianni, P., Petrou, M., Kittler, J.V.,
Mixture-Models with Higher-Order Moments,
GeoRS(35), No. 2, March 1997, pp. 341-353.
IEEE Top Reference. 9704
BibRef

Bosdogianni, P., Petrou, M., Kittler, J.V.,
Mixed Pixel Classification with Robust Statistics,
GeoRS(35), No. 3, May 1997, pp. 551-559.
IEEE Top Reference. 9706
BibRef
Earlier:
Mixed Pixel Classification in Remote Sensing,
SPIE(2315), Image and Signal Processing for Remote Sensing, Rome, September 1994, pp. 494-505. BibRef

Bosdogianni, P., Kalviainen, H., Petrou, M., Kittler, J.V.,
Robust Unmixing of Large Sets of Mixed Pixels,
PRL(18), No. 5, May 1997, pp. 415-424. 9708
BibRef

Bosdogianni, P., Petrou, M., Kittler, J.V.,
Classification of Sets of Mixed Pixels with the Hypothesis-Testing Hough Transform,
VISP(145), No. 1, February 1998, pp. 57-64. 9804
See also Hough Transform Algorithm with a 2D Hypothesis-Testing Kernel, A. BibRef

Kalviainen, H., Bosdogianni, P., Petrou, M., Kittler, J.V.,
Mixed Pixel Classification with the Randomized Hough Transform,
ICPR96(II: 576-580).
IEEE DOI 9608
(Univ. of Surrey, UK) BibRef

Lang, G.K., Seitz, P.,
Robust Classification of Arbitrary Object Classes Based on Hierarchical Spatial Feature-Matching,
MVA(10), No. 3, 1997, pp. 123-135.
Springer DOI 9709
BibRef

Kharin, Y.[Yurij], Zhuk, E.[Eugene],
Filtering of multivariate samples containing 'outliers' for clustering,
PRL(19), No. 12, 30 October 1998, pp. 1077-1085. BibRef 9810

Kharin, Y.[Yurij], Zhuk, E.[Eugene],
Robustness in statistical pattern recognition under 'contaminations' of training samples,
ICPR94(B:504-506).
IEEE DOI 9410
BibRef

Kundur, D., Hatzinakos, D., and Leung, H.,
Robust Classification of Blurred Imagery,
IP(9), No. 2, February 2000, pp. 243-255.
IEEE DOI 0003
BibRef
Earlier:
A Novel Approach to Robust Blind Classification of Remote Sensing Imagery,
ICIP97(III: 130-133).
IEEE DOI BibRef

Meer, P.[Peter], Stewart, C.V.[Charles V.], Tyler, D.E.[David E.],
Robust Computer Vision: An Interdisciplinary Challenge,
CVIU(78), No. 1, April 2000, pp. 1-7.
DOI Link
HTML Version. Robust Techniques. Special Issue introduction. 0004
BibRef

Meer, P.[Peter],
From a robust hierarchy to a hierarchy of robustness,
FIU01(323-347).
HTML Version. BibRef 0100

Kim, M.H.[Mun-Hwa], Jang, D.S.[Dong-Sik], Yang, Y.K.[Young-Kyu],
A robust-invariant pattern recognition model using Fuzzy ART,
PR(34), No. 8, August 2001, pp. 1685-1696.
WWW Link. 0105
BibRef

Jiang, M.F., Tseng, S.S., Su, C.M.,
Two-phase clustering process for outliers detection,
PRL(22), No. 6-7, May 2001, pp. 691-700.
Elsevier DOI 0105
BibRef

Shoham, S.[Shy],
Robust clustering by deterministic agglomeration EM of mixtures of multivariate t-distributions,
PR(35), No. 5, May 2002, pp. 1127-1142.
WWW Link. 0202
BibRef

Ramaswamy, S.[Sridhar], Rastogi, R.[Rajeev], Shim, K.[Kyuseok],
Efficient algorithms for mining outliers from large data sets,
ACM SIGMOD(29), No. 2, June 2000, pp. 427-438.
WWW Link. Formulation for distance based outliers. BibRef 0006

Li, Y.H.[Yu-Hua], Pont, M.J.[Michael J.], Jones, N.B.[N. Barrie],
Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where 'unknown' faults may occur,
PRL(23), No. 5, March 2002, pp. 569-577.
Elsevier DOI 0202
BibRef

Miller, D.J., Browning, J.,
A mixture model and EM-based algorithm for class discovery, robust classification, and outlier rejection in mixed labeled/unlabeled data sets,
PAMI(25), No. 11, November 2003, pp. 1468-1483.
IEEE Abstract. 0311
Augment the training set with unlabeled examples, assumed to come from a know class or a completely new class. Robust analysis. BibRef

He, Z.Y.[Zeng-You], Xu, X.F.[Xiao-Fei], Deng, S.C.[Sheng-Chun],
Discovering cluster-based local outliers,
PRL(24), No. 9-10, June 2003, pp. 1641-1650.
WWW Link. 0304
BibRef

Shekhar, S.[Shashi], Lu, C.T.[Chang-Tien], Zhang, P.S.[Pu-Sheng],
A Unified Approach to Detecting Spatial Outliers,
GeoInfo(7), No. 2, June 2003, pp. 139-166.
DOI Link 0307
BibRef

Wang, Z.D.[Zi-Dong], Liu, X.H.[Xiao-Hui],
Robust stability of two-dimensional uncertain discrete systems,
SPLetters(10), No. 5, May 2003, pp. 133-136.
IEEE Top Reference. 0304
BibRef
And: Corrections: SPLetters(10), No. 8, August 2003, pp. 250-250.
IEEE Abstract. 0308
BibRef

Sebe, N.[Nicu], Lew, M.S.[Michael S.],
Robust Computer Vision Theory and Applications,
KluwerApril 2003. ISBN 1-4020-1293-4.
WWW Link. BibRef 0304

Hu, T.M.[Tian-Ming], Sung, S.Y.[Sam Y.],
Detecting pattern-based outliers,
PRL(24), No. 16, December 2003, pp. 3059-3068.
WWW Link. 0310
BibRef

Zhang, J.S.[Jiang-She], Leung, Y.W.[Yiu-Wing],
Robust clustering by pruning outliers,
SMC-B(33), No. 6, December 2003, pp. 983-999.
IEEE Abstract. 0401
BibRef

Ouyang, S., Ching, P.C., Lee, T.,
Robust adaptive quasi-Newton algorithms for eigensubspace estimation,
VISP(150), No. 4, October 2003, pp. 321-330.
IEEE Abstract. 0401
BibRef

Li, Y.M.[Yong-Min],
On incremental and robust subspace learning,
PR(37), No. 7, July 2004, pp. 1509-1518.
WWW Link. 0405
BibRef

Meer, P.[Peter],
Robust Techniques for Computer Vision,
ETCV04(Chapter 4). BibRef 0400

Grinstead, B.[Brad], Koschan, A.F.[Andreas F.], Gribok, A.V.[Andrei V.], Abidi, M.A.[Mongi A.], Gorsich, D.[David],
Outlier rejection by oriented tracks to aid pose estimation from video,
PRL(27), No. 1, 1 January 2006, pp. 37-48.
WWW Link. 0512
BibRef

Ma, J.H.[Jiang-Hong], Leung, Y.[Yee], Luo, J.C.[Jian-Cheng],
A highly robust estimator for regression models,
PRL(27), No. 1, 1 January 2006, pp. 29-36.
WWW Link. 0512
BibRef

Kim, J.H.[Jae-Hak], Han, J.H.[Joon H.],
Outlier correction from uncalibrated image sequence using the Triangulation method,
PR(39), No. 3, March 2006, pp. 394-404.
WWW Link. 0601
BibRef

Fidler, S.[Sanja], Skocaj, D.[Danijel], Leonardis, A.[Aleš],
Combining Reconstructive and Discriminative Subspace Methods for Robust Classification and Regression by Subsampling,
PAMI(28), No. 3, March 2006, pp. 337-350.
IEEE DOI 0602
PCA can help in reconstructing missing data. LDA for classification. BibRef

Skocaj, D.[Danijel], Leonardis, A.[Aleš], Bischof, H.[Horst],
Weighted and robust learning of subspace representations,
PR(40), No. 5, May 2007, pp. 1556-1569.
WWW Link. 0702
BibRef
Earlier: A1, A2, Only:
Weighted and robust incremental method for subspace learning,
ICCV03(1494-1501).
IEEE DOI 0311
Appearance-based modeling; Robust learning; Principal component analysis; Weighted PCA; Missing pixels; Robust PCA BibRef

Skocaj, D.[Danijel], Leonardis, A.[Ales],
Incremental and robust learning of subspace representations,
IVC(26), No. 1, 1 January 2008, pp. 27-38.
WWW Link. 0711
Subspace learning; Incremental learning; Robust learning BibRef

Skocaj, D.[Danijel], Leonardis, A.[Aleš],
Robust recognition and pose determination of 3-D objects using range images in eigenspace approach,
3DIM01(171-178).
IEEE DOI 0106
BibRef

Franti, P.[Pasi], Virmajoki, O.[Olli], Hautamaki, V.,
Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph,
PAMI(28), No. 11, November 2006, pp. 1875-1881.
IEEE DOI 0609
BibRef

Hautamaki, V.[Ville], Kinnunen, T.[Tomi], Franti, P.[Pasi],
Text-independent speaker recognition using graph matching,
PRL(29), No. 9, 1 July 2008, pp. 1427-1432.
Elsevier DOI 0711
Affine transformation invariance; Graph matching; Structural matching; kNN graph; Clustering; Speaker recognition BibRef

Hautamaki, V., Karkkainen, I., Franti, P.,
Outlier detection using k-nearest neighbour graph,
ICPR04(III: 430-433).
IEEE DOI 0409
BibRef

Hillenbrand, U.[Ulrich],
Consistent parameter clustering: Definition and analysis,
PRL(28), No. 9, 1 July 2007, pp. 1112-1122.
WWW Link. 0704
Robust estimation; Clustering; Hough transform; Statistical consistency BibRef

Hoseinnezhad, R.[Reza], Bab-Hadiashar, A.[Alireza],
Consistency of robust estimators in multi-structural visual data segmentation,
PR(40), No. 12, December 2007, pp. 3677-3690.
WWW Link. 0709
BibRef
And:
A Novel High Breakdown M-estimator for Visual Data Segmentation,
ICCV07(1-6).
IEEE DOI 0710
Robust scale estimation; Robust model fitting; Consistent estimators BibRef

Hoseinnezhad, R.[Reza], Bab-Hadiashar, A.[Alireza],
An M-estimator for high breakdown robust estimation in computer vision,
CVIU(115), No. 8, August 2011, pp. 1145-1156.
Elsevier DOI 1101
Image segmentation; Image motion analysis; Optimization methods; Parameter estimation BibRef

Bab-Hadiashar, A.[Alireza], Hoseinnezhad, R.[Reza],
Bridging Parameter and Data Spaces for Fast Robust Estimation in Computer Vision,
DICTA08(1-8).
IEEE DOI 0812
BibRef

Hoseinnezhad, R.[Reza], Bab-Hadiashar, A.[Alireza],
Multi-Bernoulli sample consensus for simultaneous robust fitting of multiple structures in machine vision,
SIViP(9), No. 7, October 2015, pp. 1727-1736.
WWW Link. 1509
BibRef

Bandyopadhyay, S.[Sanghamitra], Santra, S.[Santanu],
A genetic approach for efficient outlier detection in projected space,
PR(41), No. 4, April 2008, pp. 1338-1349.
WWW Link. 0801
Deviation detection; Gene expression; Genetic algorithm; Grid count tree; Projected dimension; Outlier BibRef

Chen, Y.X.[Yi-Xin], Dang, X.[Xin], Peng, H.X.[Han-Xiang], Bart, Jr., H.L.[Henry L.],
Outlier Detection with the Kernelized Spatial Depth Function,
PAMI(31), No. 2, February 2009, pp. 288-305.
IEEE DOI 0901
Outliers in input data. BibRef

Teng, F.[Fei], Chen, Y.X.[Yi-Xin], Dang, X.[Xin],
Multiclass classification with potential function rules: Margin distribution and generalization,
PR(45), No. 1, 2012, pp. 540-551.
Elsevier DOI 1410
Multiclass classification BibRef

Subbarao, R.[Raghav], Meer, P.[Peter],
Nonlinear Mean Shift over Riemannian Manifolds,
IJCV(84), No. 1, August 2009, pp. xx-yy.
Springer DOI 0905
BibRef
Earlier:
Discontinuity Preserving Filtering over Analytic Manifolds,
CVPR07(1-6).
IEEE DOI 0706
BibRef
Earlier:
Nonlinear Mean Shift for Clustering over Analytic Manifolds,
CVPR06(I: 1168-1175).
IEEE DOI 0606
BibRef
And:
Subspace Estimation Using Projection Based M-Estimators over Grassmann Manifolds,
ECCV06(I: 301-312).
Springer DOI 0608
BibRef
Earlier:
Heteroscedastic Projection Based M-Estimators,
EEMCV05(III: 38-38).
IEEE DOI 0507
projection based estimator to eliminate RANSAC problems. BibRef

Subbarao, R.[Raghav], Genc, Y.[Yakup], Meer, P.[Peter],
Robust unambiguous parametrization of the essential manifold,
CVPR08(1-8).
IEEE DOI 0806
BibRef
Earlier:
Nonlinear Mean Shift for Robust Pose Estimation,
WACV07(6-6).
IEEE DOI 0702
BibRef

Lee, H.J.[Hyun-Jung], Seo, Y.D.[Yong-Duek], Lee, S.W.[Sang Wook],
Removing outliers by minimizing the sum of infeasibilities,
IVC(28), No. 6, June 2010, pp. 881-889.
Elsevier DOI 1003
The L-infinity optimization; Outlier removal; The sum of infeasibilities BibRef

Polikar, R.[Robi], DePasquale, J.[Joseph], Mohammed, H.S.[Hussein Syed], Brown, G.[Gavin], Kuncheva, L.I.[Ludmilla I.],
Learn++.MF: A random subspace approach for the missing feature problem,
PR(43), No. 11, November 2010, pp. 3817-3832.
Elsevier DOI 1008
Missing data; Missing features; Ensemble of classifiers; Random subspace method BibRef

Szeto, C.C.[Chi-Cheong], Hung, E.[Edward],
Mining outliers with faster cutoff update and space utilization,
PRL(31), No. 11, 1 August 2010, pp. 1292-1301.
Elsevier DOI 1008
Outlier detection; Distance-based outliers; Disk-based algorithms; Memory optimization See also Efficient algorithms for mining outliers from large data sets. BibRef

Masnadi-Shirazi, H.[Hamed], Vasconcelos, N.M.[Nuno M.],
Cost-Sensitive Boosting,
PAMI(33), No. 2, February 2011, pp. 294-309.
IEEE DOI 1101
losses minimized, emphaxize neighborhood of target boundary. BibRef

Masnadi-Shirazi, H.[Hamed], Mahadevan, V.[Vijay], Vasconcelos, N.M.[Nuno M.],
On the design of robust classifiers for computer vision,
CVPR10(779-786).
IEEE DOI Video of talk:
WWW Link. 1006
BibRef

Alipanahi, B.[Babak], Ghodsi, A.[Ali],
Guided Locally Linear Embedding,
PRL(32), No. 7, 1 May 2011, pp. 1029-1035.
Elsevier DOI 1101
Supervised dimensionality reduction; Locally Linear Embedding; Classification; Pattern recognition BibRef

Bhattacharyya, R.[Ramkishore],
Isolating top-k dense regions with filtration of sparse background,
PRL(32), No. 13, 1 October 2011, pp. 1554-1563.
Elsevier DOI 1109
Cohesion; Core clustering; Cohesive clusters; Top-k clustering Find the optimal subset of points that cluster properly. BibRef

Jiang, F.[Feng], Sui, Y.F.[Yue-Fei], Cao, C.[Cungen],
A hybrid approach to outlier detection based on boundary region,
PRL(32), No. 14, 15 October 2011, pp. 1860-1870.
Elsevier DOI 1110
Outlier detection; Rough sets; Boundary; Distance; KDD BibRef

Yu, S.[Stella],
Angular Embedding: A Robust Quadratic Criterion,
PAMI(34), No. 1, January 2012, pp. 158-173.
IEEE DOI 1112
given pairwise local ordering, find global ordering. Outlier removal. BibRef

Yu, J.[Jun], Lin, F.[Feng], Seah, H.S.[Hock-Soon], Li, C.H.[Cui-Hua], Lin, Z.Y.[Zi-Yu],
Image classification by multimodal subspace learning,
PRL(33), No. 9, 1 July 2012, pp. 1196-1204.
Elsevier DOI 1202
Subspace; Image classification; Semi-supervised learning; Multimodality BibRef

Kalina, J.[Jan],
Implicitly Weighted Methods in Robust Image Analysis,
JMIV(44), No. 3, November 2012, pp. 449-462.
WWW Link. 1209
BibRef

Ma, J.[Jiayi], Zhao, J.[Ji], Tian, J.W.[Jin-Wen], Bai, X.[Xiang], Tu, Z.W.[Zhuo-Wen],
Regularized vector field learning with sparse approximation for mismatch removal,
PR(46), No. 12, 2013, pp. 3519-3532.
Elsevier DOI 1308
Vector field learning BibRef

Zhao, J.[Ji], Ma, J.[Jiayi], Tian, J.W.[Jin-Wen], Ma, J.[Jie], Zhang, D.[Dazhi],
A robust method for vector field learning with application to mismatch removing,
CVPR11(2977-2984).
IEEE DOI 1106
Vector Field Consensus (VFC). Distinguish inliers from outliers. BibRef

Rasheed, F., Alhajj, R.,
A Framework for Periodic Outlier Pattern Detection in Time-Series Sequences,
Cyber(44), No. 5, May 2014, pp. 569-582.
IEEE DOI 1405
data mining BibRef

Zhong, F.J.[Fu-Jin], Li, D.F.[De-Fang], Zhang, J.S.[Jia-Shu],
Robust locality preserving projection based on maximum correntropy criterion,
JVCIR(25), No. 7, 2014, pp. 1676-1685.
Elsevier DOI 1410
Locality preserving projections BibRef

Liu, T., Tao, D.,
Classification with Noisy Labels by Importance Reweighting,
PAMI(38), No. 3, March 2016, pp. 447-461.
IEEE DOI 1602
Algorithm design and analysis. Sample labels are randomly corrupted. BibRef

Deng, Y.[Yue], Bao, F.[Feng], Deng, X.S.[Xue-Song], Wang, R.P.[Rui-Ping], Kong, Y.Y.[You-Yong], Dai, Q.H.[Qiong-Hai],
Deep and Structured Robust Information Theoretic Learning for Image Analysis,
IP(25), No. 9, September 2016, pp. 4209-4221.
IEEE DOI 1609
biological tissues BibRef

Li, J.Y.[Jia-Yuan], Hu, Q.[Qingwu], Ai, M.Y.[Ming-Yao], Zhong, R.F.[Ruo-Fei],
Robust feature matching via support-line voting and affine-invariant ratios,
PandRS(132), No. 1, 2017, pp. 61-76.
Elsevier DOI 1710
Robust feature matching BibRef

Domingues, R.[Rémi], Filippone, M.[Maurizio], Michiardi, P.[Pietro], Zouaoui, J.[Jihane],
A comparative evaluation of outlier detection algorithms: Experiments and analyses,
PR(74), No. 1, 2018, pp. 406-421.
Elsevier DOI 1711
Outlier detection BibRef


Wang, Y.L.[Yu-Long], Tang, Y.Y.[Yuan Yan], Li, L.Q.[Luo-Qing], Wang, P.[Patrick],
Information-theoretic atomic representation for robust pattern classification,
ICPR16(3685-3690)
IEEE DOI 1705
Computational modeling, Databases, Face recognition, Robustness, Training, data BibRef

Huang, W.[Wei], Yue, X.D.[Xiao-Dong], Zhong, C.[Caiming], Zhang, N.[Nan],
Rough Neighborhood Covering Reduction for robust classification,
ICPR16(3308-3313)
IEEE DOI 1705
Algorithm design and analysis, Approximation algorithms, Classification algorithms, Data models, Robustness, Rough sets, Uncertainty BibRef

Vinh, N.X.[Nguyen Xuan], Erfani, S., Paisitkriangkrai, S., Bailey, J., Leckie, C., Ramamohanarao, K.,
Training robust models using Random Projection,
ICPR16(531-536)
IEEE DOI 1705
Artificial neural networks, Data models, Learning systems, Robustness, Training, Training data BibRef

Piotto, N.[Nicola], Cordara, G.[Giovanni],
Statistical modelling for enhanced outlier detection,
ICIP14(4280-4284)
IEEE DOI 1502
Covariance matrices BibRef

Li, Y.Q.[Ye-Qing], Chen, C.[Chen], Yang, F.[Fei], Huang, J.Z.[Jun-Zhou],
Deep sparse representation for robust image registration,
CVPR15(4894-4901)
IEEE DOI 1510
BibRef
And: A1, A2, A4, Only:
Transformation-Invariant Collaborative Sub-representation,
ICPR14(3738-3743)
IEEE DOI 1412
Accuracy BibRef

Hou, J.[Jian], E, X.[Xu], Chi, L.[Lei], Xia, Q.[Qi], Qi, N.M.[Nai-Ming],
Robust Clustering Based on Dominant Sets,
ICPR14(1466-1471)
IEEE DOI 1412
Clustering algorithms BibRef

Liu, W.[Wei], Hua, G.[Gang], Smith, J.R.[John R.],
Unsupervised One-Class Learning for Automatic Outlier Removal,
CVPR14(3826-3833)
IEEE DOI 1409
One-Class Learning; Outlier Removal BibRef

Lee, K.H.[Kwang Hee], Lee, S.W.[Sang Wook],
Deterministic Fitting of Multiple Structures Using Iterative MaxFS with Inlier Scale Estimation,
ICCV13(41-48)
IEEE DOI 1403
MaxFS; fitting of multiple strucutres; inlier scale Robust fitting with outliers. BibRef

Hou, J.[Jian], Xu, E., Chi, L.[Lei], Xia, Q.[Qi], Qi, N.M.[Nai-Ming],
DSET: A robust clustering algorithm,
ICIP13(3795-3799)
IEEE DOI 1402
clustering BibRef

Goldstein, M.[Markus],
FastLOF: An Expectation-Maximization based Local Outlier detection algorithm,
ICPR12(2282-2285).
WWW Link. 1302
BibRef

Huang, D.[Dong], Cabral, R.S.[Ricardo Silveira], de la Torre, F.[Fernando],
Robust Regression,
ECCV12(IV: 616-630).
Springer DOI 1210
BibRef

Lu, C.Y.[Can-Yi], Min, H.[Hai], Zhao, Z.Q.[Zhong-Qiu], Zhu, L.[Lin], Huang, D.S.[De-Shuang], Yan, S.C.[Shui-Cheng],
Robust and Efficient Subspace Segmentation via Least Squares Regression,
ECCV12(VII: 347-360).
Springer DOI 1210
BibRef

Gao, Y.[Yan], Li, Y.Q.[Yi-Qun],
Improving Gaussian Process Classification with Outlier Detection, with Applications in Image Classification,
ACCV10(IV: 153-164).
Springer DOI 1011
BibRef

Evans, H., Zhang, M.,
Particle swarm optimisation for object classification,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Seo, Y.D.[Yong-Duek], Lee, H.J.[Hyun-Jung], Lee, S.W.[Sang Wook],
Outlier Removal by Convex Optimization for L-Infinity Approaches,
PSIVT09(203-214).
Springer DOI 0901
BibRef

Bauckhage, C.[Christian],
Probabilistic Diffusion Classifiers for Object Detection,
ICPR08(1-4).
IEEE DOI 0812
BibRef
Earlier:
Robust Tensor Classifiers for Color Object Recognition,
ICIAR07(352-363).
Springer DOI 0708
BibRef

Raducanu, B.[Bogdan], Vitriŕ, J.[Jordi],
Incremental Subspace Learning for Cognitive Visual Processes,
BVAI07(214-223).
Springer DOI 0710
BibRef

Ferraz, L., Felip, R., Martínez, B., Binefa, X.,
A Density-Based Data Reduction Algorithm for Robust Estimators,
IbPRIA07(II: 355-362).
Springer DOI 0706
BibRef

Xiong, L.[Liang], Li, J.G.[Jian-Guo], Zhang, C.S.[Chang-Shui],
Discriminant Additive Tangent Spaces for Object Recognition,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Khurd, P.[Parmeshwar], Baloch, S.H.[Sajjad H.], Gur, R.[Ruben], Davatzikos, C.[Christos], Verma, R.[Ragini],
Manifold Learning Techniques in Image Analysis of High-dimensional Diffusion Tensor Magnetic Resonance Images,
ComponentAnalysis07(1-7).
IEEE DOI 0706
BibRef

Duin, R.P.W.[Robert P. W.], Fred, A.L.N.[Ana L.N.], Loog, M.[Marco], Pekalska, E.[El˙zbieta],
Mode Seeking Clustering by KNN and Mean Shift Evaluated,
SSSPR12(51-59).
Springer DOI 1211
BibRef

Tax, D.M.J.[David M. J.], Juszczak, P.[Piotr], Pekalska, E.[El˙zbieta], Duin, R.P.W.[Robert P. W.],
Outlier Detection Using Ball Descriptions with Adjustable Metric,
SSPR06(587-595).
Springer DOI 0608
BibRef

Colliez, J., Dufrenois, F., Hamad, D.,
Robust Regression and Outlier Detection with SVR: Application to Optic Flow Estimation,
BMVC06(III:1229).
PDF File. 0609
BibRef

Hu, J.Y.[Jian-Ying], Ray, B.[Bonnie], Han, L.[Lanshan],
An Interweaved HMM/DTW Approach to Robust Time Series Clustering,
ICPR06(III: 145-148).
IEEE DOI 0609
BibRef

Zheng, W.M.[Wen-Ming], Tang, X.[Xiaoou],
A Robust Algorithm for Generalized Orthonormal Discriminant Vectors,
ICPR06(II: 784-787).
IEEE DOI 0609
BibRef

Felsberg, M.[Michael], Granlund, G.H.[Gosta H.],
P-Channels: Robust Multivariate M-Estimation of Large Datasets,
ICPR06(III: 262-267).
IEEE DOI 0609
BibRef

Yang, F.W.[Fu-Wen], Lin, H.J.[Hwei-Jen], Wang, P.S.P.[Patrick S. P.], Wu, H.H.[Hung-Hsuan],
Robust Clustering based on Winner-Population Markov Chain,
ICPR06(II: 589-592).
IEEE DOI 0609
BibRef

Cao, W.B.[Wen-Bo], Haralick, R.M.[Robert M.],
Nonlinear Manifold Clustering By Dimensionality,
ICPR06(I: 920-924).
IEEE DOI 0609
BibRef

Sim, K.[Kristy], Hartley, R.[Richard],
Removing Outliers Using The L-inf Norm,
CVPR06(I: 485-494).
IEEE DOI 0606
See also Recovering Camera Motion Using L-inf Minimization. BibRef

Hou, X.W.[Xin-Wen], Liu, C.L.[Cheng-Lin], Tan, T.N.[Tie-Niu],
Learning Boosted Asymmetric Classifiers for Object Detection,
CVPR06(I: 330-338).
IEEE DOI 0606
BibRef

Kaufhold, J.[John], Abbott, J.[Justin], Kaucic, R.[Robert],
Distributed Cost Boosting and Bounds on Mis-classification Cost,
CVPR06(I: 146-153).
IEEE DOI 0606
Cost sensitive boosting for industrial applications. BibRef

den Hollander, R.J.M., Hanjalic, A.,
Outlier identification in stereo correspondences using quadrics,
BMVC05(xx-yy).
HTML Version. 0509
Robust method for computing epipolar geometry from matches. BibRef

Yan, W.[Wang], Liu, Q.S.[Qing-Shan], Lu, H.Q.[Han-Qing], Ma, S.D.[Song-De],
Multiple Similarities Based Kernel Subspace Learning for Image Classification,
ACCV06(II:244-253).
Springer DOI 0601
BibRef

Grossmann, E.[Etienne],
AdaTree: Boosting a Weak Classifier into a Decision Tree,
LCV04(105).
IEEE DOI 0406
BibRef

Souvenir, R.[Richard], Pless, R.[Robert],
Manifold Clustering,
ICCV05(I: 648-653).
IEEE DOI 0510
Separating intersecting classes. BibRef

Herbin, S.,
Robust multihypothesis discrimination of controlled I.I.D. processes,
ICPR04(I: 200-203).
IEEE DOI 0409
BibRef

Chen, H.F.[Hai-Feng], Shimshoni, I., Meer, P.,
Model based object recognition by robust information fusion,
ICPR04(III: 57-60).
IEEE DOI 0409
BibRef

Ying, Z.[Zhao], Keong, K.C.[Kwoh Chee],
Fast leave-one-out evaluation and improvement on inference for LS-SVMs,
ICPR04(III: 494-497).
IEEE DOI 0409
BibRef

Park, J.H.[Jin-Hyeong], Zhang, Z.Y.[Zhen-Yue], Zha, H.Y.[Hong-Yuan], Kasturi, R.,
Local smoothing for manifold learning,
CVPR04(II: 452-459).
IEEE DOI 0408
Weighted smoothing for outlier detection. Build on weighted PCA. BibRef

Chen, H.F.[Hai-Feng], Meer, P.,
Robust regression with projection based m-estimators,
ICCV03(878-885).
IEEE DOI 0311
BibRef

Lepetit, V., Shahrokni, A., Fua, P.,
Robust data association for online applications,
CVPR03(I: 281-288).
IEEE DOI 0307
BibRef

Choukroun, A.[Ariel], Charvillat, V.[Vincent],
Bucketing Techniques in Robust Regression for Computer Vision,
SCIA03(609-616).
Springer DOI 0310
BibRef

Ben Hamza, A.[Abdessamad], Krim, H.,
Robust influence functionals for image filtering,
ICIP03(III: 361-364).
IEEE DOI 0312
See also Geodesic Matching of Triangulated Surfaces. BibRef

Izquierdo, E.[Ebroul],
A Highly Robust Regressor and its Application in Computer Vision,
BMVC00(xx-yy).
PDF File. 0009
BibRef

Myatt, D.R., Torr, P.H.S.[Philip H.S.], Nasuto, S.J., Bishop, J.M., Craddock, R.,
NAPSAC: High Noise, High Dimensional Robust Estimation - it's in the Bag,
BMVC02(Computer Vision Tools). 0208
BibRef

Comby, F.[Frederic], Strauss, O.[Olivier], Aldon, M.J.[Marie-José],
Possibility Theory and Rough Histograms for Motion Estimation in a Video Sequence,
VF01(473 ff.).
Springer DOI 0209
BibRef

Strauss, O., Comby, F., Aldon, M.J.,
Rough Histograms for Robust Statistics,
ICPR00(Vol II: 684-687).
IEEE DOI 0009
BibRef

Barakat, H., Blostein, D.,
Training with positive and negative data samples: Effects on a classifier for hand-drawn geometric shapes,
ICDAR01(1017-1021).
IEEE DOI 0109
BibRef

Ohya, J., Sengupta, K.,
Generating Virtual Environments for Human Communications: Virtual Metamorphosis System and Novel View Generation,
CVVRHC98(Sensing and Rendering Real Scenes). BibRef 9800

Bischof, H.[Horst], Leonardis, A.[Ales], Pezzei, F.[Florian],
A Robust Subspace Classifier,
ICPR98(Vol I: 114-116).
IEEE DOI 9808
BibRef

Schunck, B.G.[Brian G.],
Robust Computational Vision,
Robust90(xx). BibRef 9000

Zhuang, X.H.[Xin-Hua], and Haralick, R.M.[Robert M.],
Developing Robust Techniques for Computer Vision,
Robust90(xx). BibRef 9000

Chen, C.H.[Chien-Huei], and Mulgaonkar, P.G.[Prasanna G.],
Robust Vision-Programs Based on Statistical Feature Measurements,
Robust90(xx). BibRef 9000

Brailovsky, V.L.,
An Approach to Outlier Detection Based on Bayesian Probabilistic Model,
ICPR96(II: 70-74).
IEEE DOI 9608
(Tel-Aviv Univ., IL) BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Boosting, AdaBoost Technique .


Last update:Dec 7, 2017 at 17:23:10