Shared-Neighbours methods for visual content structuring and mining

[1]  Michael Isard,et al.  Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[2]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[3]  Massih-Reza Amini,et al.  Multi-view clustering of multilingual documents , 2010, SIGIR.

[4]  D.M. Mount,et al.  An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Winston H. Hsu,et al.  Query expansion for hash-based image object retrieval , 2009, ACM Multimedia.

[6]  Hongbin Wang,et al.  Fuzzy nearest neighbor clustering of high-dimensional data , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[7]  Charu C. Aggarwal,et al.  On the Surprising Behavior of Distance Metrics in High Dimensional Spaces , 2001, ICDT.

[8]  Christopher J. C. Burges,et al.  Spectral clustering and transductive learning with multiple views , 2007, ICML '07.

[9]  Christoph H. Lampert,et al.  Unsupervised Object Discovery: A Comparison , 2010, International Journal of Computer Vision.

[10]  Tsuhan Chen,et al.  A Topic-Motion Model for Unsupervised Video Object Discovery , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Nilesh V. Patel,et al.  Multimedia Data Mining: An Overview , 2007 .

[12]  Alexei A. Efros,et al.  Discovering objects and their location in images , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[13]  Douglas L. Miller,et al.  Robust Inference With Multiway Clustering , 2011 .

[14]  Andrew Zisserman,et al.  Geometric LDA: A Generative Model for Particular Object Discovery , 2008, BMVC.

[15]  Pietro Perona,et al.  Towards automatic discovery of object categories , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[16]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[17]  Russell C. Eberhart,et al.  Gene clustering using self-organizing maps and particle swarm optimization , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[18]  Wen Gao,et al.  Towards semantic embedding in visual vocabulary , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Alfred Kobsa,et al.  The Adaptive Web, Methods and Strategies of Web Personalization , 2007, The Adaptive Web.

[20]  Antonio Criminisi,et al.  Object categorization by learned universal visual dictionary , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[21]  M. R. Brito,et al.  Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection , 1997 .

[22]  Isabelle Tellier,et al.  Cascade Evaluation of Clustering Algorithms , 2006, ECML.

[23]  J. A. Hartigan,et al.  A k-means clustering algorithm , 1979 .

[24]  Alexei A. Efros,et al.  Discovering object categories in image collections , 2005 .

[25]  Sudipto Guha,et al.  CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.

[26]  Charles Elkan,et al.  Using the Triangle Inequality to Accelerate k-Means , 2003, ICML.

[27]  Edward Y. Chang,et al.  Parallel Spectral Clustering in Distributed Systems , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Thomas Hofmann,et al.  Unsupervised Learning by Probabilistic Latent Semantic Analysis , 2004, Machine Learning.

[29]  Andrew Zisserman,et al.  Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[30]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[31]  Marcel Worring,et al.  Browsing visual collections using graphs , 2007, MIR '07.

[32]  David Nistér,et al.  Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[33]  Pavel Berkhin,et al.  A Survey of Clustering Data Mining Techniques , 2006, Grouping Multidimensional Data.

[34]  Djemel Ziou,et al.  Image Retrieval from the World Wide Web: Issues, Techniques, and Systems , 2004, CSUR.

[35]  Wei-Ying Ma,et al.  Grouping web image search result , 2004, MULTIMEDIA '04.

[36]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[37]  Cordelia Schmid,et al.  Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search , 2008, ECCV.

[38]  Mikhail Belkin,et al.  Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.

[39]  Philippe Montesinos,et al.  A Fast Matching Method for Color Uncalibrated Images using Differential Invariants , 1998, BMVC.

[40]  Bernt Schiele,et al.  Multiple Object Class Detection with a Generative Model , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[41]  Shih-Fu Chang,et al.  A utility framework for the automatic generation of audio-visual skims , 2002, MULTIMEDIA '02.

[42]  Ron Bekkerman,et al.  Multi-modal Clustering for Multimedia Collections , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[43]  Andrew Zisserman,et al.  Object Mining Using a Matching Graph on Very Large Image Collections , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.

[44]  Ravi Kumar,et al.  Connectivity structure of bipartite graphs via the KNC-plot , 2008, WSDM '08.

[45]  Andrew Zisserman,et al.  Near Duplicate Image Detection: min-Hash and tf-idf Weighting , 2008, BMVC.

[46]  Ray A. Jarvis,et al.  Clustering Using a Similarity Measure Based on Shared Near Neighbors , 1973, IEEE Transactions on Computers.

[47]  Eamonn J. Keogh,et al.  Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases , 2001, Knowledge and Information Systems.

[48]  Nozha Boujemaa,et al.  Multi-source shared nearest neighbours for multi-modal image clustering , 2010, Multimedia Tools and Applications.

[49]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[50]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[51]  Luc Van Gool,et al.  Video mining with frequent itemset configurations , 2006 .

[52]  L. A. Goodman.  On the Exact Variance of Products , 1960 .

[53]  L. Moisan,et al.  Maximal meaningful events and applications to image analysis , 2003 .

[54]  Olivier Buisson,et al.  Logo retrieval with a contrario visual query expansion , 2009, ACM Multimedia.

[55]  Luc Van Gool,et al.  Modeling scenes with local descriptors and latent aspects , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[56]  Huan Liu,et al.  Subspace clustering for high dimensional data: a review , 2004, SKDD.

[57]  M. Fiedler.  Algebraic connectivity of graphs , 1973 .

[58]  Nozha Boujemaa,et al.  Visual-based plant species identification from crowdsourced data , 2011, ACM Multimedia.

[59]  Meng Wang,et al.  Visual query suggestion , 2010, ACM Trans. Multim. Comput. Commun. Appl..

[60]  Guillaume Pitel,et al.  Image clustering based on a shared nearest neighbors approach for tagged collections , 2008, CIVR '08.

[61]  Yi Liu,et al.  Automated Vocabulary Acquisition and Interpretation in Multimodal Conversational Systems , 2007, ACL.

[62]  Guillermo Sapiro,et al.  Supervised Dictionary Learning , 2008, NIPS.

[63]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[64]  Luc Van Gool,et al.  Mining from large image sets , 2009, CIVR '09.

[65]  David G. Lowe,et al.  Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration , 2009, VISAPP.

[66]  Vipin Kumar,et al.  Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data , 2003, SDM.

[67]  Joachim M. Buhmann,et al.  Stability-Based Validation of Clustering Solutions , 2004, Neural Computation.

[68]  Dan Frankowski,et al.  Collaborative Filtering Recommender Systems , 2007, The Adaptive Web.

[69]  J. A. Spierenburg,et al.  VOICI: Video Overview for Image Cluster Indexing -- a swift browsing tool for a large digital image database using similarities , 1997, BMVC.

[70]  László Lovász,et al.  Random Walks on Graphs: A Survey , 1993 .

[71]  Levent Ertoz,et al.  A New Shared Nearest Neighbor Clustering Algorithm and its Applications , 2002 .

[72]  Jing Liu,et al.  Hierarchical clustering-based navigation of image search results , 2008, ACM Multimedia.

[73]  Massih-Reza Amini,et al.  Exploiting Visual Concepts to Improve Text-Based Image Retrieval , 2009, ECIR.

[74]  Fan Chung,et al.  Spectral Graph Theory , 1996 .

[75]  Alexis Joly,et al.  New local descriptors based on dissociated dipoles , 2007, CIVR '07.

[76]  Jeremy Buhler,et al.  Efficient large-scale sequence comparison by locality-sensitive hashing , 2001, Bioinform..

[77]  David R. Karger,et al.  A new approach to the minimum cut problem , 1996, JACM.

[78]  Gabriela Csurka,et al.  Adapted Vocabularies for Generic Visual Categorization , 2006, ECCV.

[79]  Anil K. Jain,et al.  Writer adaptation of online handwriting models , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

[80]  Santosh S. Vempala,et al.  On clusterings: Good, bad and spectral , 2004, JACM.

[81]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[82]  Narendra Ahuja,et al.  Extracting Subimages of an Unknown Category from a Set of Images , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[83]  Jiayu Tang,et al.  Non-negative matrix factorisation for object class discovery and image auto-annotation , 2008, CIVR '08.

[84]  Tian Zhang,et al.  BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.

[85]  Dorothea Wagner,et al.  Between Min Cut and Graph Bisection , 1993, MFCS.

[86]  W. Eric L. Grimson,et al.  Spatial Latent Dirichlet Allocation , 2007, NIPS.

[87]  Mohan S. Kankanhalli,et al.  Multimedia data mining: state of the art and challenges , 2010, Multimedia Tools and Applications.

[88]  Ray A. Jarvis,et al.  Robust and efficient cluster analysis using a shared near neighbours approach , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[89]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[90]  Santosh S. Vempala,et al.  On clusterings-good, bad and spectral , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[91]  Alexander Hauptmann,et al.  Meta-Classification of Multimedia Classifiers , 2002, KDMCD.

[92]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[93]  Andrew Zisserman,et al.  Video data mining using configurations of viewpoint invariant regions , 2004, CVPR 2004.

[94]  William M. Rand,et al.  Objective Criteria for the Evaluation of Clustering Methods , 1971 .

[95]  Sudipto Guha,et al.  ROCK: A Robust Clustering Algorithm for Categorical Attributes , 2000, Inf. Syst..

[96]  Trevor Darrell,et al.  Unsupervised Learning of Categories from Sets of Partially Matching Image Features , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[97]  Junlin Zhou,et al.  Spectral clustering algorithm based on adaptive neighbor distance sort order , 2010, The 3rd International Conference on Information Sciences and Interaction Sciences.

[98]  Cordelia Schmid,et al.  A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.

[99]  John Nerbonne,et al.  Bipartite spectral graph partitioning to co-cluster varieties and sound correspondences in dialectology , 2009, Graph-based Methods for Natural Language Processing.

[100]  Dimitrios Gunopulos,et al.  Automatic subspace clustering of high dimensional data for data mining applications , 1998, SIGMOD '98.

[101]  Lotfi A. Zadeh,et al.  Fuzzy Algorithms , 1968, Inf. Control..

[102]  Joseph T. Chang,et al.  Spectral biclustering of microarray data: coclustering genes and conditions. , 2003, Genome research.

[103]  Yixin Chen,et al.  Content-based image retrieval by clustering , 2003, MIR '03.

[104]  James Ze Wang,et al.  Image retrieval: Ideas, influences, and trends of the new age , 2008, CSUR.

[105]  Inderjit S. Dhillon,et al.  Co-clustering documents and words using bipartite spectral graph partitioning , 2001, KDD '01.

[106]  Patrick Bouthemy,et al.  Space-time A Contrario Clustering for Detecting Coherent Motions , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[107]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[108]  Wei-Ying Ma,et al.  Hierarchical clustering of WWW image search results using visual, textual and link information , 2004, MULTIMEDIA '04.

[109]  Jiri Matas,et al.  Large-Scale Discovery of Spatially Related Images , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[110]  Frédéric Jurie,et al.  Creating efficient codebooks for visual recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[111]  M. E. Houle.  The Relevant‐Set Correlation Model for Data Clustering , 2008, Stat. Anal. Data Min..

[112]  D. Christodoulakis,et al.  Customer clustering using RFM analysis , 2005 .

[113]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[114]  Franciska de Jong,et al.  Multimedia Search Without Visual Analysis: The Value of Linguistic and Contextual Information , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[115]  Ming-Syan Chen,et al.  Dual Clustering: Integrating Data Clustering over Optimization and Constraint Domains , 2005, IEEE Trans. Knowl. Data Eng..

[116]  Alexei A. Efros,et al.  Unsupervised discovery of visual object class hierarchies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[117]  Lionel Moisan,et al.  Edge Detection by Helmholtz Principle , 2001, Journal of Mathematical Imaging and Vision.

[118]  Nicu Sebe,et al.  Content-based multimedia information retrieval: State of the art and challenges , 2006, TOMCCAP.

[119]  Andrei Z. Broder,et al.  On the resemblance and containment of documents , 1997, Proceedings. Compression and Complexity of SEQUENCES 1997 (Cat. No.97TB100171).

[120]  Ulrike von Luxburg,et al.  How the result of graph clustering methods depends on the construction of the graph , 2011, ArXiv.

[121]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[122]  Nozha Boujemaa,et al.  The Pl@ntnet project: plant computational identification and collaborative information system , 2011 .

[123]  Xiaoying Gao,et al.  QC4 - A Clustering Evaluation Method , 2007, PAKDD.

[124]  Djoerd Hiemstra,et al.  PFTijah: text search in an XML database system , 2006 .

[125]  Jianbo Shi,et al.  A Random Walks View of Spectral Segmentation , 2001, AISTATS.

[126]  Jiri Matas,et al.  Geometric min-Hashing: Finding a (thick) needle in a haystack , 2009, CVPR.

[127]  Aidong Zhang,et al.  Cluster analysis for gene expression data: a survey , 2004, IEEE Transactions on Knowledge and Data Engineering.

[128]  Mor Naaman,et al.  Generating diverse and representative image search results for landmarks , 2008, WWW.

[129]  H Kawaji,et al.  A graph-based clustering method for a large set of sequences using a graph partitioning algorithm. , 2001, Genome informatics. International Conference on Genome Informatics.

[130]  Cedric Nishan Canagarajah,et al.  A Unified Framework for Object Retrieval and Mining , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[131]  Yanchun Zhang,et al.  Co-clustering Analysis of Weblogs Using Bipartite Spectral Projection Approach , 2010, KES.

[132]  Min Chen,et al.  A decision tree-based multimodal data mining framework for soccer goal detection , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[133]  Frédéric Jurie,et al.  Fast Discriminative Visual Codebooks using Randomized Clustering Forests , 2006, NIPS.

[134]  Beth Ellis,et al.  Manual of Leaf Architecture , 2009 .

[135]  Olivier Buisson,et al.  Consistent visual words mining with adaptive sampling , 2011, ICMR.

[136]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[137]  Luc Van Gool,et al.  World-scale mining of objects and events from community photo collections , 2008, CIVR '08.

[138]  Yuji Matsumoto,et al.  Using the Mutual k-Nearest Neighbor Graphs for Semi-supervised Classification on Natural Language Data , 2011, CoNLL.

[139]  Siu Cheung Hui,et al.  Mining Multiple Clustering Data for Knowledge Discovery , 2003, Discovery Science.

[140]  Chris H. Q. Ding,et al.  Bipartite graph partitioning and data clustering , 2001, CIKM '01.

[141]  Hans-Peter Kriegel,et al.  Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? , 2010, SSDBM.

[142]  Hamidah Ibrahim,et al.  A Survey: Clustering Ensembles Techniques , 2009 .

[143]  Jongho Nang,et al.  A Novel Approach to Collect Training Images from WWW for Image Thesaurus Building , 2007, 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing.

[144]  Michael Isard,et al.  Object retrieval with large vocabularies and fast spatial matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[145]  Michael Isard,et al.  Lost in quantization: Improving particular object retrieval in large scale image databases , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[146]  Gang Wang,et al.  Using Dependent Regions for Object Categorization in a Generative Framework , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[147]  Cordelia Schmid,et al.  Improving Bag-of-Features for Large Scale Image Search , 2010, International Journal of Computer Vision.

[148]  James Ze Wang,et al.  SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[149]  Riccardo Leardi,et al.  PARVUS: An Extendable Package of Programs for Data Exploration , 1988 .

[150]  Inderjit S. Dhillon,et al.  Kernel k-means: spectral clustering and normalized cuts , 2004, KDD.

[151]  Mario Vento,et al.  A Graph-Based Clustering Method and Its Applications , 2007, BVAI.

[152]  Ana L. N. Fred,et al.  Data clustering using evidence accumulation , 2002, Object recognition supported by user interaction for service robots.

[153]  M. Newman.  Properties of highly clustered networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[154]  Jonathan Goldstein,et al.  When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.

[155]  David G. Stork,et al.  Pattern classification, 2nd Edition , 2000 .

[156]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[157]  Francesco Masulli,et al.  A survey of kernel and spectral methods for clustering , 2008, Pattern Recognit..

[158]  Vipin Kumar,et al.  The Challenges of Clustering High Dimensional Data , 2004 .

[159]  Adrian E. Raftery,et al.  Model-Based Clustering, Discriminant Analysis, and Density Estimation , 2002 .

[160]  Gabriela Csurka,et al.  Visual categorization with bags of keypoints , 2002, eccv 2004.

[161]  Meng Wang,et al.  Visual query suggestion , 2009, ACM Multimedia.

[162]  F. Cao,et al.  An a contrario approach to hierarchical clustering validity assessment , 2004 .

[163]  Charles Elkan,et al.  Scalability for clustering algorithms revisited , 2000, SKDD.

[164]  Chi-Hoon Lee,et al.  On Data Clustering Analysis: Scalability, Constraints, and Validation , 2002, PAKDD.