Local Features for Image Classification

I thank everybody at the ITI who helped me make the stay in Valencia not only an academic, but also a personal experience. Especially, I would like to mention

[1]  E. Jaynes.  Information Theory and Statistical Mechanics , 1957 .

[2]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[3]  Yann LeCun,et al.  Efficient Pattern Recognition Using a New Transformation Distance , 1992, NIPS.

[4]  Yann LeCun,et al.  Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation , 1996, Neural Networks: Tricks of the Trade.

[5]  Adam L. Berger,et al.  A Maximum Entropy Approach to Natural Language Processing , 1996, CL.

[6]  Bernhard Schölkopf,et al.  Prior Knowledge in Support Vector Kernels , 1997, NIPS.

[7]  Norbert Krüger,et al.  Face recognition by elastic bunch graph matching , 1997, Proceedings of International Conference on Image Processing.

[8]  Cordelia Schmid,et al.  Bayesian Decision Versus Voting for Image Retrieval , 1997, CAIP.

[9]  Adwait Ratnaparkhi,et al.  A Simple Introduction to Maximum Entropy Models for Natural Language Processing , 1997 .

[10]  Sunil Arya,et al.  An optimal algorithm for approximate nearest neighbor searching fixed dimensions , 1998, JACM.

[11]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Cordelia Schmid,et al.  A structured probabilistic model for recognition , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[13]  Thomas Martin Deserno,et al.  Survey: interpolation methods in medical image processing , 1999, IEEE Transactions on Medical Imaging.

[14]  Michael E. Tipping.  The Relevance Vector Machine , 1999, NIPS.

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

[16]  Daniel Keysers.  Approaches to Invariant Image Object Recognition , 2000 .

[17]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Hermann Ney,et al.  Invariant image object recognition using mixture densities , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[19]  Jitendra Malik,et al.  Shape Context: A New Descriptor for Shape Matching and Object Recognition , 2000, NIPS.

[20]  Hermann Ney,et al.  Experiments with an extended tangent distance , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[21]  Hermann Ney,et al.  Automatic Classification of Red Blood Cells Using Gaussian Mixture Densities , 2000, Bildverarbeitung für die Medizin.

[22]  Heinrich Niemann,et al.  Appearance-Based Statistical Object Recognition by Heterogeneous Background and Occlusions , 2001, DAGM-Symposium.

[23]  Stan Z. Li,et al.  Learning representative local features for face detection , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[24]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[25]  Juan Carlos Pérez-Cortes,et al.  Local Representations and a direct Voting Scheme for Face Recognition , 2001, PRIS.

[26]  J. van Leeuwen,et al.  Audio- and Video-Based Biometric Person Authentication , 2001, Lecture Notes in Computer Science.

[27]  Hermann Ney,et al.  Invariant Classification of Red Blood Cells , 2001 .

[28]  Hermann Ney,et al.  Maximum Entropy and Gaussian Models for Image Object Recognition , 2002, DAGM-Symposium.

[29]  Matthew A. Brown,et al.  Invariant Features from Interest Point Groups , 2002, BMVC.

[30]  Hermann Ney,et al.  Classification of Medical Images Using local Representations , 2002, Bildverarbeitung für die Medizin.

[31]  William H. Press,et al.  Numerical recipes in C , 2002 .

[32]  Hermann Ney,et al.  Combination of Tangent Vectors and Local Representations for Handwritten Digit Recognition , 2002, SSPR/SPR.

[33]  Hermann Ney,et al.  Statistical framework for model-based image retrieval in medical applications , 2003, J. Electronic Imaging.

[34]  Thomas Deselaers,et al.  Features for Image Retrieval , 2003 .

[35]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[36]  Luc Vandendorpe,et al.  Face Verification Competition on the XM2VTS Database , 2003, AVBPA.

[37]  Hermann Ney,et al.  Local Representations for Multi-object Recognition , 2003, DAGM-Symposium.

[38]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[39]  Hermann Ney,et al.  Statistical Image Object Recognition using Mixture Densities , 2001, Journal of Mathematical Imaging and Vision.

[40]  Martin Werner,et al.  Digitale Bildverarbeitung , 2021 .