13.4 Object Recognition, General Techniques

13.4.1 Invariants -- Eigen Representations, General Appearance Based Methods

Al-Shaykh, O.K., Doherty, J.F.,
Invariant Image-Analysis Based on Radon-Transform and SVD,
CirSysSignal(43), No. 2, February 1996, pp. 123-133. 9703
SVD. BibRef

Murase, H., and Nayar, S.K.,
Visual Learning And Recognition Of 3-D Objects From Appearance,
IJCV(14), No. 1, January 1995, pp. 5-24.
Springer DOI
PDF File. BibRef 9501
Earlier:
Visual Learning Object Models from Appearance,
DARPA93(547-555). BibRef
And:
Learning and Recognition of 3D Objects from Appearance,
WQV93(39-50). BibRef
And:
Learning Object Models from Appearance,
AAAI-93(836-843) Model Acquisition. A new representation that is parameterized by pose and illumination. BibRef

Murase, H., Nayar, S.K.,
Detection of 3D Objects in Cluttered Scenes Using Hierarchical Eigenspace,
PRL(18), No. 4, April 1997, pp. 375-384. 9708
BibRef
Earlier:
Learning by a Generation Approach to Appearance-Based Object Recognition,
ICPR96(I: 24-29).
IEEE DOI 9608
BibRef
Earlier:
Image Spotting of 3D Objects Using Parametric Eigenspace Representation,
SCIA95(325-332). BibRef

Murase, H., Shi, M.[Musashino], Nayar, S.K.,
Parametric Eigenspace Representation for Visual Learning and Recognition,
SPIE(2031), 1993, pp. 378-391. BibRef 9300

Murase, H.[Hiroshi], Nayar, S.K.[Shree K.], and Nene, S.A.[Sameer A.],
Software Library for Appearance Matching (SLAM),
ARPA94(I:733-737).
PDF File. Code, Matching.
WWW Link. BibRef 9400

Nayar, S.K.[Shree K.], Nene, S.A.[Sameer A.], Murase, H.,
Real-Time 100 Object Recognition System,
ARPA96(1223-1228). BibRef 9600
And: CRA96(III: 2321-2325).
PDF File. Generate Eigen space representation of the object. BibRef

Nene, S.A.[Sameer A.], Nayar, S.K.[Shree K.],
Closest Point Search in High Dimensions,
CVPR96(859-865).
IEEE DOI 100 object recognition and other applications. BibRef 9600

Nayar, S.K.[Shree K.], Nene, S.A.[Sameer A.], Murase, H.[Hiroshi],
Subspace Methods for Robot Vision,
RA(12), No. 5, October 1996, pp. 750-758. 9610
BibRef
Earlier: A3, A1, A2:
General Learning Algorithm for Robot Vision,
ARPA94(I:753-763). System: SLAM. Software Library for Appearance Matching BibRef

Mukherjee, S.[Sayan], Nayar, S.K.[Shree K.],
Optimal RBF Networks for Visual Learning,
ICCV95(794-800).
IEEE DOI BibRef 9500

Paatero, P., and Tapper, U.,
Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values,
Environmetrics(5), 1994, 111-126. BibRef 9400

Flusser, J.,
Object Matching by Means of Matching Likelihood Coefficients,
PRL(16), 1995, pp. 893-900. BibRef 9500

Chalmond, B.[Bernard], Girard, S.C.[Stephane C.],
Nonlinear Modeling of Scattered Multivariate Data and Its Application to Shape Change,
PAMI(21), No. 5, May 1999, pp. 422-432.
IEEE DOI PCA has problems. Introduce a non-linear "PCA" process. BibRef 9905

Huttenlocher, D.P., Lilien, R.H., Olson, C.F.,
View-Based Recognition Using an Eigenspace Approximation to the Hausdorff Measure,
PAMI(21), No. 9, September 1999, pp. 951-955.
IEEE DOI
PDF File.
PDF File. BibRef 9909
Earlier:
Approximate Hausdorff Matching Using Eigenspaces,
ARPA96(1181-1186). BibRef
And:
Object Recognition Using Subspace Methods,
ECCV96(I:536-545).
Springer DOI To counter the problems of view based (eigenspace) approaches when there are occlusions, an eigenspace approximation to the Hausdorff measure. Applies to edge maps. BibRef

Leonardis, A.[Ales], Bischof, H.[Horst],
Robust Recognition Using Eigenimages,
CVIU(78), No. 1, April 2000, pp. 99-118. 0004

DOI Link BibRef
Earlier:
Computational complexity reduction in eigenspace approaches,
CAIP97(1-8).
Springer DOI 9709
Instead of computing coefficients with a projection of the data onto the eigenimages, extract them with a hypothesize-and-test using subsets of image points. Select from compteing hypotheses using the MDL principle.
See also Efficient MDL-Based Construction of RBF Networks, An. BibRef

Bischof, H.[Horst], Leonardis, A.[Ales],
Robust Recognition of Scaled Eigenimages Through a Hierarchical Approach,
CVPR98(664-670).
IEEE DOI Estimate both the scale of the object and the coefficients of the eigenimages. BibRef 9800

Leonardis, A.[Ales], Bischof, H.[Horst], Maver, J.[Jasna],
Multiple eigenspaces,
PR(35), No. 11, November 2002, pp. 2613-2627.
Elsevier DOI 0208
BibRef

Maver, J.[Jasna], Leonardis, A.[Ales],
Recognizing 2-tone images in grey-level parametric eigenspaces,
PRL(23), No. 14, December 2002, pp. 1631-1640.
Elsevier DOI 0208
BibRef

Leonardis, A.[Ales], Bischof, H.[Horst],
Multiple Eigenspaces by MDL,
ICPR00(Vol I: 233-237).
IEEE DOI 0009
BibRef

Leonardis, A.[Ales], Bischof, H.[Horst],
Robust Recovery of Eigneimages in the Presence of Outliers and Occlusions,
JCIT(4), No. 1, 1996, pp. 25-36. BibRef 9600
Earlier:
Dealing with Occlusions in the Eigenspace Approach,
CVPR96(453-458).
IEEE DOI BibRef

Sengel, M., Berger, M., Kravtchenko-Berejnoi, V., Bischof, H.,
Fast object recognition and pose determination,
ICIP02(III: 349-352).
IEEE DOI 0210
BibRef

Skoaj, D., Bischof, H., Leonardis, A.,
A Robust PCA Algorithm for Building Representations from Panoramic Images,
ECCV02(IV: 761 ff.).
Springer DOI 0205
BibRef

Bischof, H.[Horst], Wildenauer, H.[Horst], Leonardis, A.[Ales],
Illumination insensitive recognition using eigenspaces,
CVIU(95), No. 1, July 2004, pp. 86-104.
Elsevier DOI 0407
BibRef
Earlier:
Illumination Insensitive Eigenspaces,
ICCV01(I: 233-238).
IEEE DOI 0106
Incorporate a gradient filter bank into the eigenspace recognition. BibRef

Costa, M.S.[Mauro S.], Shapiro, L.G.[Linda G.],
3D Object Recognition and Pose with Relational Indexing,
CVIU(79), No. 3, September 2000, pp. 364-407.
DOI Link 0008
BibRef
Earlier:
Scene Analysis Using Appearance-Based Models and Relational Indexing,
SCV95(103-108).
IEEE DOI University of Washington. Graph representations. Match with multiple objects in a scene. BibRef

Costa, M.S.[Mauro S.], Shapiro, L.G.[Linda G.],
Analysis of scenes containing multiple non-polyhedral 3D objects,
CIAP95(272-280).
Springer DOI 9509
BibRef

Shapiro, L.G.[Linda G.], Costa, M.S.[Mauro S.],
Appearance-based 3D object recognition,
ORCV94(51-63).
Springer DOI 9412
BibRef

Ji, Q., Costa, M.S., Haralick, R.M., Shapiro, L.G.,
An Integrated Linear Technique for Pose Estimation from Different Geometric Features,
PRAI(13), No. 5, August 1999, pp. 705. 0005
BibRef

Mustafa, A.A.Y.[Adnan A.Y.], Shapiro, L.G.[Linda G.], and Ganter, M.A.[Mark A.],
Matching Surface Signatures for Object Identification,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Borotschnig, H., Paletta, L., Prantl, M., Pinz, A.J.,
Appearance-based active object recognition,
IVC(18), No. 9, June 2000, pp. 715-727.
Elsevier DOI 0004
BibRef
Earlier:
Active Object Recognition in Parametric Eigenspace,
BMVC98(xx-yy). BibRef

Paletta, L.[Lucas], Fritz, G.[Gerald], Seifert, C.[Christin],
Perception-Action Based Object Detection from Local Descriptor Combination and Reinforcement Learning,
SCIA05(639-648).
Springer DOI 0506
BibRef
And:
Cascaded Sequential Attention for Object Recognition with Informative Local Descriptors and Q-learning of Grouping Strategies,
AttenPerf05(III: 94-94).
IEEE DOI 0507
BibRef

Greindl, C., Goyal, A., Ogris, G., Paletta, L.,
Cascaded attention and grouping for object recognition from video,
CIAP03(448-453).
IEEE DOI 0310
BibRef

Fritz, G., Paletta, L., Bischof, H.,
Object recognition using local information content,
ICPR04(II: 15-18).
IEEE DOI 0409
BibRef

Hornegger, J.[Joachim], Niemann, H.[Heinrich], Risack, R.[Robert],
Appearance-based object recognition using optimal feature transforms,
PR(33), No. 2, February 2000, pp. 209-224.
Elsevier DOI 0001
BibRef

Reinhold, M.P., Paulus, D., Niemann, H.,
Improved Appearance-Based 3-D Object Recognition Using Wavelet Features,
VMV01(xx-yy).
PDF File. 0209
BibRef
And:
Appearance-Based Statistical Object Recognition by Heterogenous Background and Occlusions,
DAGM01(254-261).
PS File. BibRef

Reinhold, M.P.[Michael P.], Grzegorzek, M.[Marcin], Denzler, J.[Joachim], Niemann, H.[Heinrich],
Appearance-based recognition of 3-D objects by cluttered background and occlusions,
PR(38), No. 5, May 2005, pp. 739-753.
Elsevier DOI 0501
BibRef

Grzegorzek, M.[Marcin], Niemann, H.[Heinrich],
Statistical Object Recognition Including Color Modeling,
ICIAR05(481-489).
Springer DOI 0509
BibRef

Worthington, P.L.[Philip L.], Hancock, E.R.[Edwin R.],
Object Recognition Using Shape-from-Shading,
PAMI(23), No. 5, May 2001, pp. 535-542.
IEEE DOI 0105
BibRef
Earlier:
Structural Object Recognition Using Shape-from-shading,
ICPR00(Vol I: 738-741).
IEEE DOI 0009
BibRef
And:
Histogram-based Object Recognition using Shape-from-Shading,
CVPR00(I: 643-648).
IEEE DOI 0005
BibRef
Earlier:
Region-based Object Recognition using Shape-from-Shading,
ECCV00(I: 455-471).
Springer DOI 0003
Can surface topography from SfS be used for object recognition?
See also Facial Shape-from-shading and Recognition Using Principal Geodesic Analysis and Robust Statistics. BibRef

Worthington, P.L.[Philip L.], Hancock, E.R.[Edwin R.],
Synthesising Appearance Manifolds using Shape-from-Shading,
SCIA01(P-W4A). 0206
BibRef

Hancock, E.R.[Edwin R.], Worthington, P.L.[Philip L.], Huet, B.[Benoit],
Appearance-Based Object Recognition Using Shape-From-Shading,
ICPR98(Vol I: 412-416).
IEEE DOI 9808
BibRef
And: A2, A3, A1:
Increased Extent of Characteristic Views using Shape-from-shading for Object Recognition,
BMVC98(xx-yy). BibRef

Agarwal, M.[Mohit], Jain, G.[Gaurav], Chaudhury, S.[Santanu],
Indexing for local appearance-based recognition of planar objects,
PRL(23), No. 1-3, January 2002, pp. 311-317.
Elsevier DOI 0201
BibRef

Zhang, Z.F.M.[Zhong-Fei Mark], Srihari, R.K.[Rohini K.],
Subspace morphing theory for appearance based object identification,
PR(35), No. 11, November 2002, pp. 2389-2396.
Elsevier DOI 0208
BibRef

Zhang, Z.F.[Zhong-Fei], Srihari, R.K.[Rohini K.],
Computer based method and apparatus for object recognition,
US_Patent6,636,619, Oct 21, 2003
WWW Link. BibRef 0310

Quick, P.[Philip], Capson, D.W.[David W.],
Subspace position measurement in the presence of occlusion,
PRL(23), No. 14, December 2002, pp. 1721-1733.
Elsevier DOI 0208
Camera or object position with eigen based method. BibRef

Stegmann, M.B.[Mikkel B.], Larsen, R.[Rasmus],
Multi-band modelling of appearance,
IVC(21), No. 1, January 2003, pp. 61-67.
Elsevier DOI 0301
BibRef

Stegmann, M.B.[Mikkel B.], Ersboll, B.K.[Bjarne K.], Larsen, R.[Rasmus],
Fame: A flexible appearance modeling environment,
MedImg(22), No. 10, October 2003, pp. 1319-1331.
IEEE Abstract. 0310
BibRef

Darkner, S.[Sune], Larsen, R.[Rasmus], Stegmann, M.B.[Mikkel B.], Ersboll, B.K.[Bjarne K.],
Wedgelet Enhanced Appearance Models,
GenModel04(177).
IEEE DOI 0406
BibRef

Larsen, R.[Rasmus], Stegmann, M.B.[Mikkel B.], Darkner, S.[Sune], Forchhammer, S.[Soren], Cootes, T.F.[Timothy F.], Ersboll, B.K.[Bjarne Kjaer],
Texture enhanced appearance models,
CVIU(106), No. 1, April 2007, pp. 20-30.
Elsevier DOI 0704
Registration; Dimensionality reduction; Atlases; Deformable models; Active appearance models; Wavelets; Wedgelets; Face images BibRef

Chen, C.S.[Chu-Song], Hsieh, W.T.[Wen-Teng], Chen, J.H.[Jiun-Hung],
Panoramic Appearance-Based Recognition of Video Contents Using Matching Graphs,
SMC-B(34), No. 1, February 2004, pp. 179-199.
IEEE Abstract. 0403
BibRef

Chen, C.S.[Chu-Song], Chen, J.H.[Jiun-Hung], Hsieh, W.T.[Wen-Teng],
A dynamic programming approach for appearance-based recognition of environments,
ICPR02(II: 893-896).
IEEE DOI 0211
BibRef

Min, W.L.[Wan-Li], Lu, K.[Ke], He, X.F.[Xiao-Fei],
Locality pursuit embedding,
PR(37), No. 4, April 2004, pp. 781-788.
Elsevier DOI 0403
Linear embedding that respects the local geometrical structure described by the Euclidean distances. Rather than PCA for dimensionality reduction. BibRef

Chen, J.H.[Jiun-Hung], Chen, C.S.[Chu-Song],
Object Recognition Based on Image Sequences by Using Inter-Feature-Line Consistencies,
PR(37), No. 9, September 2004, pp. 1913-1923.
Elsevier DOI 0407
BibRef
Earlier:
Using Inter-feature-Line Consistencies for Sequence-Based Object Recognition,
ECCV04(Vol I: 108-120).
Springer DOI 0405
Appearance-based recognition in sequences. Derived from nearest feature line.
See also Performance Evaluation of the Nearest Feature Line Method in Image Classification and Retrieval. BibRef

Bicego, M.[Manuele], Danese, S.[Stefano], Melzi, S.[Simone], Castellani, U.[Umberto],
A Bioinformatics Approach to 3D Shape Matching,
NORDIA14(313-325).
Springer DOI 1504
BibRef

van de Weijer, J., Gevers, T., Smeulders, A.W.M.,
Robust Photometric Invariant Features From the Color Tensor,
IP(15), No. 1, January 2006, pp. 118-127.
IEEE DOI 0601
BibRef

Autio, I.[Ilkka],
Using natural class hierarchies in multi-class visual classification,
PR(39), No. 7, July 2006, pp. 1290-1299.
Elsevier DOI 0606
Multi-object recognition; Hierarchic object recognition; Efficient object recognition BibRef

Verbeek, J.[Jakob],
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models,
PAMI(28), No. 8, August 2006, pp. 1236-1250.
IEEE DOI 0606
Appearence based models. BibRef

Zivkovic, Z.[Zoran], Verbeek, J.[Jakob],
Transformation invariant component analysis for binary images,
CVPR06(I: 254-259).
IEEE DOI 0606
BibRef

Khabou, M.A., Hermi, L., Rhouma, M.B.H.,
Shape recognition using eigenvalues of the Dirichlet Laplacian,
PR(40), No. 1, January 2007, pp. 141-153.
Elsevier DOI 0611
Shape recognition; Eigenvalues; Laplacian; Fixed membrane problem; Dirichlet boundary condition; Neural networks BibRef

Choi, H.[Heeyoul], Choi, S.J.[Seung-Jin],
Robust kernel Isomap,
PR(40), No. 3, March 2007, pp. 853-862.
Elsevier DOI 0611
Isomap; Kernel PCA; Manifold learning; Multidimensional scaling (MDS); Nonlinear dimensionality reduction BibRef

Bishnu, A.[Arijit], Bhattacharya, B.B.,
Stacked Euler Vector (SERVE): A Gray-Tone Image Feature Based on Bit-Plane Augmentation,
PAMI(29), No. 2, February 2007, pp. 350-355.
IEEE DOI 0701
SERVE is a four-tuple, each integer representing the Euler number of the partial binary image formed by pixel overlap relations among the four most significant bit planes of the gray-tone image. Apply to
See also Columbia Object Image Library (COIL-100). BibRef

Sun, T.[Tingkai], Chen, S.C.[Song-Can],
Locality preserving CCA with applications to data visualization and pose estimation,
IVC(25), No. 5, 1 May 2007, pp. 531-543.
Elsevier DOI 0703
Canonical correlation analysis (CCA); Locality preservation; Pose estimation; Data visualization; Dimensionality reduction CCA (for dimensionality reduction) applied to image recognition. BibRef

Vik, T.[Torbjorn], Heitz, F.[Fabrice], Charbonnier, P.[Pierre],
Robust Pose Estimation and Recognition Using Non-Gaussian Modeling of Appearance Subspaces,
PAMI(29), No. 5, May 2007, pp. 901-905.
IEEE DOI 0704
Appearence model generalizes the Gaussian subspace model to non-Gaussian and nonparametric distributions. BibRef

Dahyot, R.[Rozenn], Charbonnier, P.[Pierre], Heitz, F.[Fabrice],
Robust Visual Recognition of Color Images,
CVPR00(I: 685-690).
IEEE DOI 0005
BibRef

Wang, X.[Xuan], Xiao, B.[Bin], Ma, J.F.[Jian-Feng], Bi, X.L.[Xiu-Li],
Scaling and rotation invariant analysis approach to object recognition based on Radon and Fourier-Mellin transforms,
PR(40), No. 12, December 2007, pp. 3503-3508.
Elsevier DOI 0709
Radon, then Fourier-Mellin. To get invariants. Radon transform; Pattern recognition; Fourier-Mellin transform; Invariant analysis BibRef

Wang, X.[Xuan], Guo, F.X.[Fang-Xia], Xiao, B.[Bin], Ma, J.F.[Jian-Feng],
Rotation invariant analysis and orientation estimation method for texture classification based on Radon transform and correlation analysis,
JVCIR(21), No. 1, January 2010, pp. 29-32.
Elsevier DOI 1002
Correlation analysis; Radon transform; Rotation invariance; Texture analysis; Orientation estimation BibRef

Mansur, A.[Al], Kuno, Y.[Yoshinori],
Specific and Class Object Recognition for Service Robots through Autonomous and Interactive Methods,
IEICE(E91-D), No. 6, June 2008, pp. 1793-1803.
DOI Link 0806
BibRef

Mansur, A.[Al], Sakata, K.[Katsutoshi], Das, D.[Dipankar], Kuno, Y.[Yoshinori],
Recognition of Plain Objects Using Local Region Matching,
IEICE(E91-D), No. 7, July 2008, pp. 1906-1913.
DOI Link 0807
BibRef
Earlier: A1, A2, A4, Only:
Recognition of Household Objects by Service Robots Through Interactive and Autonomous Methods,
ISVC07(II: 140-151).
Springer DOI 0711
BibRef

Das, D.[Dipankar], Kobayashi, Y.[Yoshinori], Kuno, Y.[Yoshinori],
Multiple Object Category Detection and Localization Using Generative and Discriminative Models,
IEICE(E92-D), No. 10, October 2009, pp. 2112-2121.
WWW Link. 0910
BibRef
Earlier:
A Hybrid Model for Multiple Object Category Detection and Localization,
MVA09(431-).
PDF File. 0905
BibRef

Das, D.[Dipankar], Kobayashi, Y.[Yoshinori], Kuno, Y.[Yoshinori],
Sub-Category Optimization through Cluster Performance Analysis for Multi-View Multi-Pose Object Detection,
IEICE(E94-D), No. 7, July 2011, pp. 1467-1478.
WWW Link. 1107
BibRef
Earlier:
Sub-Category Optimization for Multi-view Multi-pose Object Detection,
ICPR10(1405-1408).
IEEE DOI 1008
BibRef
Earlier:
Efficient Hypothesis Generation through Sub-categorization for Multiple Object Detection,
ISVC09(II: 160-171).
Springer DOI 0911
BibRef

Das, D.[Dipankar], Kobayashi, Y.[Yoshinori], Kuno, Y.[Yoshinori],
Object Detection and Localization in Clutter Range Images Using Edge Features,
ISVC09(II: 172-183).
Springer DOI 0911
BibRef

Das, D.[Dipankar], Mansur, A.[Al], Kobayashi, Y.[Yoshinori], Kuno, Y.[Yoshinori],
An Integrated Method for Multiple Object Detection and Localization,
ISVC08(II: 133-144).
Springer DOI 0812
BibRef

Mansur, A.[Al], Kuno, Y.[Yoshinori],
Improving Recognition through Object Sub-categorization,
ISVC08(II: 851-859).
Springer DOI 0812
BibRef

Mansur, A.[Al], Hossain, M.A.[Mohammed Altab], Kuno, Y.[Yoshinori],
Integration of Multiple Methods for Class and Specific Object Recognition,
ISVC06(I: 841-849).
Springer DOI 0611
BibRef

Kurnia, R.[Rahmadi], Hossain, M.A.[Mohammed Altab], Kuno, Y.[Yoshinori],
Use of Spatial Reference Systems in Interactive Object Recognition,
CRV06(62-62).
IEEE DOI 0607
BibRef

Hossain, M.A.[Mohammed Altab], Kurnia, R.[Rahmadi], Nakamura, A.[Akio], Kuno, Y.[Yoshinori],
Interactive Object Recognition through Hypothesis Generation and Confirmation,
IEICE(E89-D), No. 7, July 2006, pp. 2197-2206.
DOI Link 0607
BibRef

Hossain, M.A.[Mohammed Altab], Kurnia, R.[Rahmadi], Kuno, Y.[Yoshinori],
Geometric and Photometric Analysis for Interactively Recognizing Multicolor or Partially Occluded Objects,
ISVC05(134-142).
Springer DOI 0512
BibRef

Agarwal, A.[Ankur], Triggs, B.[Bill],
Multilevel Image Coding with Hyperfeatures,
IJCV(78), No. 1, June 2008, pp. 15-27.
Springer DOI 0803
BibRef
Earlier:
Hyperfeatures: Multilevel Local Coding for Visual Recognition,
ECCV06(I: 30-43).
Springer DOI 0608
BibRef
And: INRIARR-5655, 2005.
HTML Version. Hierarchical local appearance models. BibRef

Wilson, R.C.[Richard C.], Zhu, P.[Ping],
A study of graph spectra for comparing graphs and trees,
PR(41), No. 9, September 2008, pp. 2833-2841.
Elsevier DOI 0806
BibRef
Earlier: A2, A1:
A Study of Graph Spectra for Comparing Graphs,
BMVC05(xx-yy).
HTML Version. 0509
BibRef
And: A2, A1:
Stability of the Eigenvalues of Graphs,
CAIP05(371).
Springer DOI 0509
Graph matching; Tree matching; Shape representation; Spectrum; Features BibRef

Sidibe, D.[Desire], Montesinos, P.[Philippe], Janaqi, S.[Stefan],
Matching Local Invariant Features with Contextual Information: An Experimental Evaluation,
ELCVIA(7), No. 1, November 2008, pp. 26-39.
DOI Link 0903
BibRef

Pinz, A.J.[Axel J.], Bischof, H.[Horst], Kropatsch, W.G.[Walter G.], Schweighofer, G.[Gerald], Haxhimusa, Y.[Yll], Opelt, A.[Andreas], Ion, A.[Adrian],
Representations for Cognitive Vision: A Review of Appearance-Based, Spatio-Temporal, and Graph-Based Approaches,
ELCVIA(7), No. 2, 2008, pp. xx.
DOI Link BibRef 0800

Li, J.[Jian], Zhou, S.H.K.[Shao-Hua Kevin], Chellappa, R.[Rama],
Appearance Modeling Using a Geometric Transform,
IP(18), No. 4, April 2009, pp. 889-902.
IEEE DOI 0903
BibRef
Earlier:
Appearance Modeling Under Geometric Context,
ICCV05(II: 1252-1259).
IEEE DOI 0510
Model the parts. Other techniques become a subset of this method. BibRef

Laptev, I.[Ivan],
Improving object detection with boosted histograms,
IVC(27), No. 5, 2 April 2009, pp. 535-544.
Elsevier DOI 0904
BibRef
Earlier:
Improvements of Object Detection Using Boosted Histograms,
BMVC06(III:949).
PDF File. 0609
Object recognition; Machine learning; Histogram image features Recognize objects in a class. histograms of features in local regions. BibRef

Chen, D.T.[Da-Tong], Liu, Q.A.[Qi-Ang], Sun, M.G.[Min-Gui], Yang, J.[Jie],
Mining Appearance Models Directly From Compressed Video,
MultMed(10), No. 2, February 2008, pp. 268-276.
IEEE DOI 0905
BibRef

Koppal, S.J.[Sanjeev J.], Narasimhan, S.G.[Srinivasa G.],
Appearance Derivatives for Isonormal Clustering of Scenes,
PAMI(31), No. 8, August 2009, pp. 1375-1385.
IEEE DOI 0906
BibRef
Earlier:
Clustering Appearance for Scene Analysis,
CVPR06(II: 1323-1330).
IEEE DOI 0606
Scene points clustered by surface normals even when geometry, material, lighting are unknown. BibRef

Lu, Z.W.[Zhi-Wu], Peng, Y.X.[Yu-Xin], Ip, H.H.S.[Horace H.S.],
Image categorization via robust pLSA,
PRL(31), No. 1, 1 January 2010, pp. 36-43.
Elsevier DOI 1001
pLSA. Image categorization; Probabilistic latent semantic analysis; Rival penalized competitive learning; Ensemble learning BibRef

Lu, Z.W.[Zhi-Wu], Peng, Y.X.[Yu-Xin], Ip, H.H.S.[Horace H.S.],
Gaussian mixture learning via robust competitive agglomeration,
PRL(31), No. 7, 1 May 2010, pp. 539-547.
Elsevier DOI 1004
Gaussian mixtures; Competitive agglomeration; Model selection; Asymptotic analysis BibRef

Lu, Z.W.[Zhi-Wu], Ip, H.H.S.[Horace H.S.],
Combining Context, Consistency, and Diversity Cues for Interactive Image Categorization,
MultMed(12), No. 3, March 2010, pp. 194-203.
IEEE DOI 1003
BibRef
Earlier:
Image categorization by learning with context and consistency,
CVPR09(2719-2726).
IEEE DOI 0906
BibRef
And:
Image categorization with spatial mismatch kernels,
CVPR09(397-404).
IEEE DOI 0906
spatial mismatch kernels for use with SVM classification. Inter-image context and cluster consistency. BibRef

Lu, Z.W.[Zhi-Wu], Ip, H.H.S.[Horace H.S.],
Spatial Markov Kernels for Image Categorization and Annotation,
SMC-B(41), No. 4, August 2011, pp. 976-989.
IEEE DOI 1108
BibRef

Wang, L.H.[Li-Hua], Lu, Z.W.[Zhi-Wu], Ip, H.H.S.[Horace H.S.],
Image Categorization Based on a Hierarchical Spatial Markov Model,
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Elsevier DOI 1003
Manifold learning; Dimensionality reduction; Maximum variance unfolding; Laplacian eigenmaps; Variance analysis BibRef

Parks, D.H.[Donovan H.], Levine, M.D.[Martin D.],
Is local colour normalization good enough for local appearance-based classification?,
MVA(21), No. 5, August 2010, pp. 789-796.
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Discriminative Learning of Local Image Descriptors,
PAMI(33), No. 1, January 2011, pp. 43-57.
IEEE DOI 1011
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ICCV07(1-8).
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Winder, S.A.J.[Simon A. J.], Brown, M.[Matthew],
Learning Local Image Descriptors,
CVPR07(1-8).
IEEE DOI 0706
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Brown, M.[Matthew], Szeliski, R.S.[Richard S.], Winder, S.A.J.[Simon A.J.],
Multi-Image Matching Using Multi-Scale Oriented Patches,
CVPR05(I: 510-517).
IEEE DOI 0507
Feature matching. Use Harris corners (
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Basri, R.[Ronen], Hassner, T.[Tal], Zelnik-Manor, L.[Lihi],
Approximate Nearest Subspace Search,
PAMI(33), No. 2, February 2011, pp. 266-278.
IEEE DOI 1101
BibRef
Earlier:
A general framework for Approximate Nearest Subspace search,
Subspace09(109-116).
IEEE DOI 0910
BibRef
Earlier:
Approximate Nearest Subspace Search with Applications to Pattern Recognition,
CVPR07(1-8).
IEEE DOI 0706
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Hoover, R.C.[Randy C.], Maciejewski, A.A.[Anthony A.], Roberts, R.G.[Rodney G.],
Eigendecomposition of Images Correlated on S^1, S^2, and SO(3) Using Spectral Theory,
IP(18), No. 11, November 2009, pp. 2562-2571.
IEEE DOI 0911
BibRef
Earlier:
An Analysis of Sphere Tessellations for Pose Estimation of 3-D Objects Using Spherically Correlated Images,
Southwest08(41-44).
IEEE DOI 0803
BibRef
And:
Aerial Pose Detection of 3-D Objects Using Hemispherical Harmonics,
Southwest08(157-160).
IEEE DOI 0803
BibRef

Hoover, R.C.[Randy C.], Maciejewski, A.A.[Anthony A.], Roberts, R.G.[Rodney G.],
Fast Eigenspace Decomposition of Images of Objects With Variation in Illumination and Pose,
SMC-B(41), No. 2, April 2011, pp. 318-329.
IEEE DOI 1103
BibRef

Gkalelis, N., Mezaris, V., Kompatsiaris, I.,
Mixture Subclass Discriminant Analysis,
SPLetters(18), No. 5, May 2011, pp. 319-322.
IEEE DOI 1104
Deal with shortcomings of subclass discriminant analysis (SDA). BibRef

Wang, C.[Can], He, X.F.[Xiao-Fei], Bu, J.J.[Jia-Jun], Chen, Z.G.[Zheng-Guang], Chen, C.[Chun], Guan, Z.Y.[Zi-Yu],
Image representation using Laplacian regularized nonnegative tensor factorization,
PR(44), No. 10-11, October-November 2011, pp. 2516-2526.
Elsevier DOI 1101
Image representation; Image clustering; Tensor; Graph Laplacian; Manifold BibRef

Chen, Y.[Yan], Zhang, J., Cai, D., Liu, W., He, X.F.[Xiao-Fei],
Nonnegative Local Coordinate Factorization for Image Representation,
IP(22), No. 3, March 2013, pp. 969-979.
IEEE DOI 1302
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Chen, Y.[Yan], Bao, H.J.[Hu-Jun], He, X.F.[Xiao-Fei],
Non-negative local coordinate factorization for image representation,
CVPR11(569-574).
IEEE DOI 1106
BibRef

Xu, Y.L.[Yi-Lei], Roy-Chowdhury, A.K.[Amit K.],
A Physics-Based Analysis of Image Appearance Models,
PAMI(33), No. 8, August 2011, pp. 1681-1688.
IEEE DOI 1107
BibRef
Earlier:
A theoretical analysis of linear and multi-linear models of image appearance,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Xu, Y.L.[Yi-Lei], Roy-Chowdhury, A.K.[Amit K.],
Learning a geometry integrated image appearance manifold from a small training set,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Do, C.M.[Cuong M.],
Improved integral imaging approach for 3D object recognition,
SPIE(Newsroom), November 17, 2011
DOI Link 1111
BibRef
And:
3D object recognition with integral imaging using neural networks,
SPIE(8135), 2011, pp. 81350D.
DOI Link A new method for displaying 3D images uses principal component analysis and neural networks to achieve accurate object recognition while reducing memory requirements and computational time. BibRef

de la Torre, F.[Fernando],
A Least-Squares Framework for Component Analysis,
PAMI(34), No. 6, June 2012, pp. 1041-1055.
IEEE DOI 1205
BibRef
Earlier:
A Least-Squares Unified View of PCA, LDA, CCA and Spectral Graph Methods,
CMU-RI-TR-08-29, May, 2008
WWW Link. BibRef
And:
Component Analysis methods for pattern recognition,
ICPR08(1-1).
IEEE DOI 0812
Analyze the representation. Relate component analysis techniques, derive numerical solutions, deal with small sample sizes, extend methods. Derive weighted generalizations of PCA, LDA, SC, and CCA, and several new CA techniques. BibRef

Miao, X.[Xu], Rahimi, A.[Ali], Rao, R.P.N.[Rajesh P.N.],
Complementary Kernel Density Estimation,
PRL(33), No. 10, 15 July 2012, pp. 1381-1387.
Elsevier DOI 1205
Generative models; Neural networks; Regression; Density estimation; Denoising; Occlusions Generative model that adopts features of discriminative models. BibRef

Miao, X.[Xu], Rao, R.P.N.[Rajesh P. N.],
Fast Structured Prediction Using Large Margin Sigmoid Belief Networks,
IJCV(99), No. 3, September 2012, pp. 302-318.
WWW Link. 1206
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Zhao, Z.Z.[Zhi-Zhen], Singer, A.[Amit],
Fourier-Bessel rotational invariant eigenimages,
JOSA-A(30), No. 5, May 2013, pp. 871-877.
WWW Link. 1305
BibRef

Lee, J.G.[Jeong-Gon], Kim, B.S.[Bum-Soo], Choi, M.J.[Mi-Jung], Moon, Y.S.[Yang-Sae],
Evaluation of Space Filling Curves for Lower-Dimensional Transformation of Image Histogram Sequences,
IEICE(E96-D), No. 10, October 2013, pp. 2277-2281.
WWW Link. 1310
Use histogram features. Very high dimensional data source. BibRef

Arandjelovic, O.D.[Ognjen D.],
Hallucinating optimal high-dimensional subspaces,
PR(47), No. 8, 2014, pp. 2662-2672.
Elsevier DOI 1405
BibRef
Earlier:
Recognition from Appearance Subspaces Across Image Sets of Variable Scale,
BMVC10(xx-yy).
HTML Version. 1009
Projection BibRef

Berger, B.[Benjamin], Vais, A.[Alexander], Wolter, F.E.[Franz-Erich],
Subimage sensitive eigenvalue spectra for image comparison,
VC(31), No. 2, February 2015, pp. 205-221.
WWW Link. 1503
BibRef

Berger, B.[Benjamin], Wolter, F.E.[Franz-Erich], Vais, A.[Alexander],
Colocalization structures and eigenvalue spectra for colour image comparison,
VC(32), No. 6-8, June 2016, pp. 1057-1067.
WWW Link. 1608
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Chen, S.B.[Si-Bao], Wang, J.[Jing], Liu, C.Y.[Cai-Yin], Luo, B.[Bin],
Two-Dimensional Discriminant Locality Preserving Projection Based on l1-norm Maximization,
PRL(87), No. 1, 2017, pp. 147-154.
Elsevier DOI 1703
Discriminant Locality Preserving Projection (DLPP) BibRef

Gasbarra, D.[Dario], Pajevic, S.[Sinisa], Basser, P.J.[Peter J.],
Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments,
SIIMS(10), No. 3, 2017, pp. 1511-1548.
DOI Link 1710
BibRef

Aujol, J.F.[Jean-Franois], Gilboa, G.[Guy], Papadakis, N.[Nicolas],
Theoretical Analysis of Flows Estimating Eigenfunctions of One-Homogeneous Functionals,
SIIMS(11), No. 2, 2018, pp. 1416-1440.
DOI Link 1807
BibRef

Chen, R.[Rui], Zhao, F.[Fei], Yang, C.S.[Chang-Shui], Li, Y.[Yuan], Huang, T.J.[Tie-Jun],
Robust estimation for image noise based on eigenvalue distributions of large sample covariance matrices,
JVCIR(63), 2019, pp. 102604.
Elsevier DOI 1909
Noise level estimation, Eigenvalue distributions, Large sample covariance matrix, Random matrix theory BibRef

Raninen, E.[Elias], Ollila, E.[Esa],
Bias Adjusted Sign Covariance Matrix,
SPLetters(29), 2022, pp. 339-343.
IEEE DOI 2202
Covariance matrices, Eigenvalues and eigenfunctions, Shape, Sensors, Indexes, Electric breakdown, Signal processing algorithms, shrinkage BibRef

Evert, E.[Eric], Vandecappelle, M.[Michiel], de Lathauwer, L.[Lieven],
Canonical Polyadic Decomposition via the Generalized Schur Decomposition,
SPLetters(29), 2022, pp. 937-941.
IEEE DOI 2205
Fundamental tensor decomposition. Tensors, Matrix decomposition, Signal processing algorithms, Eigenvalues and eigenfunctions, Standards, Optimization, Indexes, tensors BibRef

Song, Y.[Yue], Sebe, N.[Nicu], Wang, W.[Wei],
Batch-Efficient EigenDecomposition for Small and Medium Matrices,
ECCV22(XXIII:583-599).
Springer DOI 2211
BibRef

Rahman, S.[Saimunur], Wang, L.[Lei], Sun, C.M.[Chang-Ming], Zhou, L.P.[Lu-Ping],
Redro: Efficiently Learning Large-sized SPD Visual Representation,
ECCV20(XV:1-17).
Springer DOI 2011
Symmetric positive definite matrix. BibRef

Chumachenko, K.[Kateryna], Raitoharju, J.[Jenni], Gabbouj, M.[Moncef], Iosifidis, A.[Alexandros],
Incremental Fast Subclass Discriminant Analysis,
ICIP20(1771-1775)
IEEE DOI 2011
FastSDA. Kernel, Training, Feature extraction, Task analysis, Training data, Computational modeling, Data models BibRef

Yuan, G.Z.[Gan-Zhao], Shen, L.[Li], Zheng, W.S.[Wei-Shi],
A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem,
CVPR19(6106-6115).
IEEE DOI 2002
BibRef

Bungert, L.[Leon], Burger, M.[Martin], Tenbrinck, D.[Daniel],
Computing Nonlinear Eigenfunctions via Gradient Flow Extinction,
SSVM19(291-302).
Springer DOI 1909
BibRef

Streicher, O.[Or], Cohen, I.[Ido], Gilboa, G.[Guy],
BASiS: Batch Aligned Spectral Embedding Space,
CVPR23(10396-10405)
IEEE DOI 2309
BibRef

Cohen, I.[Ido], Falik, A.[Adi], Gilboa, G.[Guy],
Stable Explicit p-Laplacian Flows Based on Nonlinear Eigenvalue Analysis,
SSVM19(315-327).
Springer DOI 1909
BibRef

Muravev, A., Tran, D.T., Iosifidis, A., Kiranyaz, S., Gabbouj, M.,
Acceleration Approaches for Big Data Analysis,
ICIP18(311-315)
IEEE DOI 1809
Kernel, Matrix decomposition, Training, Computational modeling, Quantization (signal), Eigenvalues and eigenfunctions, Neural Network Acceleration BibRef

Sekikawa, Y.[Yusuke], Suzuki, K.[Koichiro], Yoshida, Y.[Yuichi], Hara, K.[Kosuke], Sato, I.[Ikuro],
Fast Eigen Matching,
BMVC16(xx-yy).
HTML Version. 1805
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Ghosh, A.[Abhijeet],
Measurement Based Appearance Modelling,
BMVC16(xx-yy).
HTML Version. 1805
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Li, Q.L.[Qi-Lin], Liu, W.Q.[Wan-Quan], Li, L.[Ling], Wang, R.H.[Ru-Hua],
Towards Large Scale Spectral Problems via Diffusion Process,
DICTA17(1-7)
IEEE DOI 1804
approximation theory, eigenvalues and eigenfunctions, extrapolation, matrix algebra, pattern clustering, Symmetric matrices BibRef

Nafees, W., Khalid, Z., Kennedy, R.A.,
Signal analysis on the ball: Design of optimal basis functions with maximal multiplicative concentration in spatial and spectral domains,
WSSIP17(1-5)
IEEE DOI 1707
Eigenvalues and eigenfunctions, Harmonic analysis, Image processing, Integral equations, Kernel, Spectral analysis, Slepian concentration problem, ball, energy concentration, localized spectral analysis, optimal basis, spatial-spectral, concentration BibRef

Boukhayma, A.[Adnane], Tsiminaki, V.[Vagia], Franco, J.S.[Jean-Sébastien], Boyer, E.[Edmond],
Eigen Appearance Maps of Dynamic Shapes,
ECCV16(I: 230-245).
Springer DOI 1611
BibRef

Hwang, S.J., Collins, M.D., Ravi, S.N., Ithapu, V.K., Adluru, N., Johnson, S.C., Singh, V.,
A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer,
ICCV15(1841-1849)
IEEE DOI 1602
Computer vision BibRef

Wu, R.B.[Ruo-Bing], Yu, Y.Z.[Yi-Zhou], Wang, W.P.[Wen-Ping],
SCaLE: Supervised and Cascaded Laplacian Eigenmaps for Visual Object Recognition Based on Nearest Neighbors,
CVPR13(867-874)
IEEE DOI 1309
deep learning BibRef

Boix, X.[Xavier], Gygli, M.[Michael], Roig, G.[Gemma], Van Gool, L.J.[Luc J.],
Sparse Quantization for Patch Description,
CVPR13(2842-2849)
IEEE DOI 1309
patch descriptor; sparse quantization BibRef

Boix, X.[Xavier], Roig, G.[Gemma], Leistner, C.[Christian], Van Gool, L.J.[Luc J.],
Nested Sparse Quantization for Efficient Feature Coding,
ECCV12(II: 744-758).
Springer DOI 1210
BibRef

Liu, G.C.[Guang-Can], Yan, S.C.[Shui-Cheng],
Latent Low-Rank Representation for subspace segmentation and feature extraction,
ICCV11(1615-1622).
IEEE DOI 1201
BibRef

Gong, Y.C.[Yun-Chao], Lazebnik, S.[Svetlana],
Comparing data-dependent and data-independent embeddings for classification and ranking of Internet images,
CVPR11(2633-2640).
IEEE DOI 1106
BibRef

Jia, K.[Ke], Wang, L.[Lei], Liu, N.J.[Nian-Jun],
Efficient Structured Support Vector Regression,
ACCV10(III: 586-598).
Springer DOI 1011
BibRef

Tompkins, F.[Frank], Wolfe, P.J.[Patrick J.],
Image analysis with regularized Laplacian eigenmaps,
ICIP10(1913-1916).
IEEE DOI 1009
BibRef

Zhao, H.T.[Hai-Tao], Sun, S.Y.[Shao-Yuan],
Optimal Locality Preserving Projection,
ICIP10(1861-1864).
IEEE DOI 1009
LPP BibRef

Li, Y.[Yin], Yan, J.C.[Jun-Chi], Zhou, Y.[Yue], Yang, J.[Jie],
Optimum Subspace Learning and Error Correction for Tensors,
ECCV10(III: 790-803).
Springer DOI 1009
BibRef

Sankaranarayanan, A.C.[Aswin C.], Veeraraghavan, A.[Ashok], Tuzel, O.[Oncel], Agrawal, A.[Amit],
Image Invariants for Smooth Reflective Surfaces,
ECCV10(II: 237-250).
Springer DOI 1009
BibRef

Xie, Y.C.[Yu-Chen], Ho, J.[Jeffrey], Vemuri, B.C.[Baba C.],
Image atlas construction via intrinsic averaging on the manifold of images,
CVPR10(2933-2939).
IEEE DOI 1006
BibRef

Chu, X.Q.[Xin-Qi], Yan, S.C.[Shui-Cheng], Li, L.Y.[Li-Yuan], Chan, K.L.[Kap Luk], Huang, T.S.[Thomas S.],
Spatialized epitome and its applications,
CVPR10(311-318).
IEEE DOI 1006
Integrate appearance and spatial arrangement of patches. BibRef

Liu, R.S.[Ri-Sheng], Su, Z.X.[Zhi-Xun], Lin, Z.C.[Zhou-Chen], Hou, X.Y.[Xiao-Yu],
Lorentzian Discriminant Projection and Its Applications,
ACCV09(III: 311-320).
Springer DOI 0909
BibRef

Eichner, M.[Marcin], Ferrari, V.[Vittorio],
Better appearance models for pictorial structures,
BMVC09(xx-yy).
PDF File. 0909
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Yang, J.[Jie], Bouzerdoum, A.[Abdesselam], Phung, S.L.[Son Lam],
A New Approach to Sparse Image Representation Using MMV and K-SVD,
ACIVS09(200-209).
Springer DOI 0909
MMV: Multiple Measurement Vectors BibRef

Gill, G.S.[Gurman S.], Levine, M.D.[Martin D.],
Multi-view Object Detection Based on Spatial Consistency in a Low Dimensional Space,
DAGM09(211-220).
Springer DOI 0909
BibRef
And:
Incorporating Shape Features in an Appearance-Based Object Detection System,
CAIP09(269-276).
Springer DOI 0909
BibRef

Gill, G.S.[Gurman S.], Levine, M.D.[Martin D.],
A Single Classifier for View-Invariant Multiple Object Class Recognition,
BMVC06(I:257).
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Butzer, J.S., Butler, A.P.H., Butler, P.H., Bones, P.J., Cook, N., Tlustos, L.,
Medipix imaging: Evaluation of datasets with PCA,
IVCNZ08(1-6).
IEEE DOI 0811
X-ray data. BibRef

Brasnett, P.[Paul], Bober, M.[Miroslaw],
Fast and robust image identification,
ICPR08(1-5).
IEEE DOI 0812
Trace transform. BibRef

Nguyen, N.[Nam], Liu, W.Q.[Wan-Quan], Venkatesh, S.[Svetha],
Ridge Regression for Two Dimensional Locality Preserving Projection,
ICPR08(1-4).
IEEE DOI 0812
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Mei, G.B.[Guo-Biao], Shelton, C.R.[Christian R.],
Unsupervised image embedding using nonparametric statistics,
ICPR08(1-4).
IEEE DOI 0812
into low dimensional space BibRef

Sharma, G.[Gaurav], Chaudhury, S.[Santanu], Srivastava1, J.B.,
Bag-of-features kernel eigen spaces for classification,
ICPR08(1-4).
IEEE DOI 0812
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Kawabata, S.[Satoshi], Hiura, S.[Shinsaku], Sato, K.[Kosuke],
A rapid anomalous region extraction method by iterative projection onto kernel eigenspace,
ICPR08(1-4).
IEEE DOI 0812
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He, Z.C.[Zhou-Can], Wang, Q.[Qing],
A Fast and Effective Dichotomy Based Hash Algorithm for Image Matching,
ISVC08(I: 328-337).
Springer DOI 0812
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Chen, W.A.[Wen-An], Zhang, H.B.[Hong-Bin],
The Condition of Kernelizing an Algorithm and an Equivalence Between Kernel Methods,
IbPRIA07(I: 338-345).
Springer DOI 0706
E.g. kernel pca. BibRef

Wolf, L.B.[Lior B.], Jhuang, H.H.[Huei-Han], Hazan, T.[Tamir],
Modeling Appearances with Low-Rank SVM,
CVPR07(1-6).
IEEE DOI 0706
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Hsiao, E.[Edward], Collet, A.[Alvaro], Hebert, M.[Martial],
Making specific features less discriminative to improve point-based 3D object recognition,
CVPR10(2653-2660).
IEEE DOI 1006
Retain ambiguity in feature matching, resolve it later in hypothesis testing phase. BibRef

de la Torre, F.[Fernando], Collet, A.[Alvaro], Quero, M.[Manuel], Cohn, J.F.[Jeffrey F.], Kanade, T.[Takeo],
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models,
CVPR07(1-8).
IEEE DOI 0706
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Felsberg, M.,
Enhanced Distribution Field Tracking Using Channel Representations,
VOT13(121-128)
IEEE DOI 1403
approximation theory
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Felsberg, M.[Michael], Hedborg, J.[Johan],
Real-Time Visual Recognition of Objects and Scenes Using P-Channel Matching,
SCIA07(908-917).
Springer DOI 0706
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Kaarna, A.[Arto], Andriyashin, A.[Alexey], Nakauchi, S.[Shigeki], Parkkinen, J.[Jussi],
Multiresolution Approach in Computing NTF,
SCIA07(334-343).
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Non-negative tensor factorization (NTF). Efficient computation. BibRef

Jain, P.K.[Paresh K.], Rao, P.K.[P. Kartik], Jawahar, C.V.,
Computing Eigen Space from Limited Number of Views for Recognition,
ICCVGIP06(662-673).
Springer DOI 0612
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Kalra, M.[Manisha], Deepti, P., Abhilash, R., Das, S.[Sukhendu],
Pose Invariant Generic Object Recognition with Orthogonal Axis Manifolds in Linear Subspace,
ICCVGIP06(619-630).
Springer DOI 0612
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Jain, V.[Varun], Zhang, H.[Hao],
Shape-Based Retrieval of Articulated 3D Models Using Spectral Embedding,
GMP06(299-312).
Springer DOI 0607
Shape retrieval. Embed the description in spectral domain, match there. BibRef

Rahman, M.M.,
Merging and Generalizing Eigenspace for Partially Occluded and Destroyed Object Recognition,
ICIP06(2729-2732).
IEEE DOI 0610
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Gonzalez-Mora, J.[Jose], Guil, N.[Nicolas], Zapata, E.L.[Emilio L.],
Tracking of Linear Appearance Models Using Second Order Minimization,
ACIVS06(1002-1013).
Springer DOI 0609
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Zhang, D.Q.[Dong-Qing], Chang, S.F.[Shih-Fu],
A Generative-Discriminative Hybrid Method for Multi-View Object Detection,
CVPR06(II: 2017-2024).
IEEE DOI 0606
Generative model structure and appearance. BibRef

Savarese, S., Winn, J., Criminisi, A.,
Discriminative Object Class Models of Appearance and Shape by Correlatons,
CVPR06(II: 2033-2040).
IEEE DOI 0606
both appearance and shape info. BibRef

Zhang, Q.N.[Qian-Ni], Izquierdo, E.[Ebroul],
A Multi-feature Optimization Approach to Object-Based Image Classification,
CIVR06(310-319).
Springer DOI 0607
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Qin, L.[Lei], Gao, W.[Wen],
Image Matching Based on A Local Invariant Descriptor,
ICIP05(III: 377-380).
IEEE DOI 0512
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He, X.F.[Xiao-Fei], Cai, D.[Deng], Yan, S.C.[Shui-Cheng], Zhang, H.J.[Hong-Jiang],
Neighborhood Preserving Embedding,
ICCV05(II: 1208-1213).
IEEE DOI 0510
Aims to preserve local structure, unlike PCA preserving global structure. BibRef

Plagemann, C.[Christian], Müller, T.[Thomas], Burgard, W.[Wolfram],
Vision-Based 3D Object Localization Using Probabilistic Models of Appearance,
DAGM05(184).
Springer DOI 0509
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Montoliu, R.[Raúl], Pla, F.[Filiberto], Klaren, A.C.[Arnoud C.],
Illumination Intensity, Object Geometry and Highlights Invariance in Multispectral Imaging,
IbPRIA05(I:36).
Springer DOI 0509
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Söderberg, R.[Robert], Nordberg, K.[Klas], Granlund, G.H.[Gösta H.],
An Invariant and Compact Representation for Unrestricted Pose Estimation,
IbPRIA05(I:3).
Springer DOI 0509
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Nordberg, K., Granlund, G.H., Knutsson, H.,
Representation and learning of invariance,
ICIP94(II: 585-589).
IEEE DOI 9411
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Xu, D.[Dong], Yan, S.C.[Shui-Cheng], Zhang, L.[Lei], Zhang, H.J.[Hong-Jiang], Liu, Z.K.[Zheng-Kai], Shum, H.Y.[Heung-Yeung],
Concurrent Subspaces Analysis,
CVPR05(II: 203-208).
IEEE DOI 0507
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Pless, R.[Robert],
Differential Structure in non-Linear Image Embedding Functions,
Non-Rigid04(10).
HTML Version. 0502
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Earlier:
Image spaces and video trajectories: Using isomap to explore video sequences,
ICCV03(1433-1440).
IEEE DOI 0311
Video as a space of possible images and a path through that space. Mappings (isomap) with deformations. BibRef

Kim, H.[Hyundo], Murphy-Chutorian, E.[Erik], Triesch, J.[Jochen],
Semi-autonomous Learning of Objects,
V4HCI06(145).
IEEE DOI 0609
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Chen, H.J.[Huei-Ju], Lee, K.C.[Kuang-Chih], Murphy-Chutorian, E.[Erik], Triesch, J.[Jochen],
Toward a Unified Probabilistic Framework for Object Recognition and Segmentation,
ISVC05(108-117).
Springer DOI 0512
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Murphy-Chutorian, E.[Erik], Triesch, J.[Jochen],
Shared Features for Scalable Appearance-Based Object Recognition,
WACV05(I: 16-21).
IEEE DOI 0502
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Thuresson, J.[Johan], Carlsson, S.[Stefan],
Appearance Based Qualitative Image Description for Object Class Recognition,
ECCV04(Vol II: 518-529).
Springer DOI 0405
Recognize classes of objects rather than individual instances. BibRef

Gvili, Y.[Yaron], Sochen, N.A.[Nir A.],
A Complete System of Measurement Invariants for Abelian Lie Transformation Groups,
ScaleSpace03(72-85).
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Build on steerable filters. BibRef

Grimes, D.B., Shon, A.P., Rao, R.P.N.,
Probabilistic bilinear models for appearance-based vision,
ICCV03(1478-1485).
IEEE DOI 0311
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Rao, R.P.N.,
Dynamic Appearance-Based Recognition,
CVPR97(540-546).
IEEE DOI 9704
Recognize with occlusions BibRef

Ababsa, F., Roussel, D., Mallem, M.,
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DAGM03(68-75).
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CVPR03(I: 803-810).
IEEE DOI 0307
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IEEE DOI 0211
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Deselaers, T.[Thomas], Keysers, D.[Daniel], Ney, H.[Hermann],
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Image Database. BibRef
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ICPR04(II: 505-508).
IEEE DOI 0409
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Maximum Entropy and Gaussian Models for Image Object Recognition,
DAGM02(498 ff.).
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Garg, G., Sharma, P.K., Chaudhury, S., Chowdhury, R.,
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ICPR02(II: 536-539).
IEEE DOI 0211
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Chennubhotla, C., Jepson, A.D., Midgley, J.,
Robust contrast-invariant eigendetection,
ICPR02(II: 745-748).
IEEE DOI 0211
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ICPR02(III: 590-594).
IEEE DOI 0211
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ICIP02(III: 313-316).
IEEE DOI 0210
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ICPR08(1-4).
IEEE DOI 0812
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Classification of Similar 3D Objects with Different Types of Features from Multi-view Images: An Approach to Classify 100 Apples,
PSIVT09(1046-1057).
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Sanei, S., Lee, T.K.,
Bayesian classification of eigencells,
ICIP02(II: 929-932).
IEEE DOI 0210
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ICPR00(Vol IV: 845-848).
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Romdhani, S., Psarrou, A., Gong, S.,
On Utilising Template and Feature-based Correspondence in Multi-view Appearance Models,
ECCV00(I: 799-813).
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Jugessur, D.[Deeptiman], Dudek, G.[Gregory],
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CVPR00(I: 834-839).
IEEE DOI 0005
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Schiele, B.[Brent], Pentland, A.P.,
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ICCV99(177-182).
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PS File. Represent objects by joint statistics of local operators. BibRef

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DARPA98(1071-1078). BibRef 9800

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BMVC00(xx-yy).
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ICPR98(Vol I: 759-761).
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CVPR98(414-420).
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ICCV90(248-256).
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CVPR97(877-883).
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CVPR98(685-691).
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CAIP99(17-24).
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Eigenstructure approach to region detection and segmentation,
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Tian, Q., Fainman, Y., Lee, S.H.,
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Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Other Sparse Coding, Low Dimensional Representation, Invariants .