IAPR

Tutorials on topics in 2D image analysis, computer vision


Online Written Course Notes

  1. General
    1. Dealing with Imprecise Spatial Information in Cognitive Vision (Isabelle Bloch)
    2. Neural nets in Vision (Roger Boyle, David Hogg)
    3. Vision Systems (A D Marshall)
    4. Vision Computacional (L. E. Sucar and G. Gomez - in Spanish)
    5. Vision Through Optimization (N. A. Thacker and T. F. Cootes)
    6. Computer Vision Online Course (Andrew Wallace)
    7. Textured Motion and Complex Motion Modeling (Yizhou Wang)
  2. Physics/Devices
    1. High dynamic range imaging for digital still camera: an overview (S. Battiato, A. Castorina, M. Mancuso)
    2. Tsai Camera Calibration Method Revisited (Interior Orientation) (Berthold K. P. Horn)
    3. Observations on the physics of imaging and image coding (Julio Marten)
  3. Representation/recognition
    1. Object Categorization (Axel Pinz)
  4. Mathematics/Geometry
    1. An Introduction to Projective Geometry (for computer vision) (Stan Birchfield)
    2. Tutorial on Rectification of Stereo Images (Andrea Fusiello)
    3. The Essential Matrix ... (Coplanarity Condition) (Berthold K. P. Horn)
    4. Quaternions and Rotation (Berthold K. P. Horn)
    5. Resources for Discrete Geometry (IAPR TC 18)
    6. Digital Geometry and Mathematical Morphology (Christer Kiselman)
    7. Linear inverse problems: A discrete presentation (Ali Mohammad-Djafari)
    8. Transforme de Radon et ses applications (French) (Ali Mohammad-Djafari)
    9. Inference bayesienne pour les problemes inverses (French) (Ali Mohammad-Djafari)
    10. Detection-Estimation (Ali Mohammad-Djafari)
    11. Problemes inverses (French) (Ali Mohammad-Djafari)
    12. Projective Geometry for Image Analysis (Roger Mohr, Bill Triggs)
    13. Monte Carlo methods (Jonathan Pengelly)
    14. Visual 3D Modeling from Images (Marc Pollefeys)
    15. Principal Components Analysis (Lindsay Smith)
    16. Fourier Analysis (Yerin Yoo)
    17. Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting (Zhengyou Zhang)
    18. Geometric Framework for Vision I: Single View and Two-View Geometry (Andrew Zisserman)
  5. Image processing/analysis
    1. Fixed Flow (Constant Optical Flow) (Berthold K. P. Horn)
    2. Optical Flow with Fixed Translation and Rotation (Berthold K. P. Horn)
    3. Principles for automatic scale selection (Tony Lindeberg)
    4. Automatic scale selection as a pre-processing stage for interpreting the visual world (Tony Lindeberg)
    5. Scale-space theory: A basic tool for analysing structures at different scales (Tony Lindeberg)
    6. A Gentle Introduction to Bilateral Filtering and its Applications (Sylvain Paris, Pierre Kornprobst, Jack Tumblin, and Frédo Durand )
  6. Applications
    1. Particle Filtering for Visual Tracking (Pedram Azad)
    2. Spatial Augmented Reality (Oliver Bimber, Ramesh Raskar, Masahiko Inami)
    3. A Tutorial on CAPTCHA - Completely Automated Public Turing test to tell Computers and Humans Apart (Theo Pavlidis)
    4. Modern Techniques In Remote Sensing (Maria Petrou)
    5. Supervised Neural Networks in Machine Vision (Neil Thacker)
    6. Performance Characterisation in Computer Vision: The Role of Statistics in Testing and Design (Neil Thacker)
    7. An Empirical Design Methodology for the Construction of Machine Vision Systems (Neil Thacker)
    8. Performance Characterisation in Computer Vision: A Guide to Best Practices (Neil Thacker)
    9. New Trends in 3D Video (Christian Theobalt, Stephan Wuermlin, Edilson de Aguiar, Christoph Niederberger)
    10. Introduction to Computer Vision from Automatic Face Analysis Viewpoint (Erno Makinen)

Online Tutorial PPT/PDF Slides

  1. General
    1. The Monogenic Framework: A Systematic Approach to Image Processing and Computer Vision (Michael Felsberg)
    2. Introduction to some aspects of biological vision (Li Zhaoping)
    3. Visual Recognition in Primates and Machines (Tomaso Poggio, Thomas Serre)
    4. Computational Photography (Ramesh Raskar, Jack Tumblin)
    5. Tutorial on Coded Light Projection Techniques (Joaquim Salvi, Jordi Pagis)
    6. The business case for implementing machine vision (PPT) - selecting a vision system from a management perspective (Nello Zuech)
  2. Physics/Devices
    1. Optics (George Barbastathis)
    2. Workshop on Diffusion Tensor Imaging (National Alliance for Medical Image Computing)
    3. Spectral color imaging (Jussi Parkkinen)
    4. Spectral image applications (Jussi Parkkinen)
    5. 8 lectures on color (Jussi Parkkinen)
  3. Representation/recognition
    1. Recognizing and Learning Object Categories (Li Fei-Fei, Rob Fergus, Antonio Torralba)
    2. Object Recognition (Li Fei-Fei)
    3. Geometric Model Acquisition (PPT) (Steve Maybank)
    4. Probabilisitic models of visual object categories (Andrew Zisserman)
    5. Template Matching Techniques in Computer Vision (Roberto Brunelli)
  4. Mathematics/Geometry
    1. Gradient Domain Manipulation Techniques in Vision and Graphics (Amit Agrawal, Ramesh Raskar)
    2. Bayesian Techniques in Vision and Perception (Olivier Aycard and Luis Enrique Sucar)
    3. Graph Cuts (Andrew Blake)
    4. Graph-Cuts versus Level-Sets (Yuri Boykov, Daniel Cremers, Vladimir Kolmogorov )
    5. Bayesian Methods for Multimedia Signal Processing (A. Taylan Cemgil)
    6. Clustering and Robust Techniques in Computer Vision (Per-Erik Forssen)
    7. Deep Belief Nets (Geoffrey Hinton)
    8. Lectures on Discrete Geometry (IAPR TC 18)
    9. Hidden Markov Models (Philip Jackson)
    10. Discrete Optimization in Computer Vision (Nikos Komodakis, Philip Torr, Vladimir Kolmogorov, Yuri Boykov)
    11. Hidden Markov Models (PPT) (Dimitrios Makris)
    12. Bayes Optimality in Pattern Recognition (Aleix Martinez)
    13. Stereo Vision: Algorithms and Applications (Stefano Mattoccia)
    14. Tensor Voting: A Perceptual Organization Approach to Computer Vision and Machine Learning (Philippos Mordohai)
    15. Tensor Methods for Machine Learning, Computer Vision, and Computer Graphics (Amnon Shashua)
  5. Image processing/analysis
    1. Graph Based Image Segmentation (Jianbo Shi, Charless Fowlkes, David Martin, Eitan Sharon)
    2. Lectures on Image Processing (Richard Peters)
    3. Texture (Mike Chantler)
  6. Applications
    1. Kernel Methods in Remote Sensing: Introduction, Applications and Research Opportunities (Gustavo Camps-Valls)
    2. Visual servoing (Francois Chaumette)
    3. Image Processing in Biomedical Applications (S. Colantonio, D. Moroni, O. Salvetti)
    4. Tutorial Medical Image Retrieval (Thomas Deselaers, Henning Muller)
    5. Iterative Methods for Image Reconstruction (Jeffrey Fessler)
    6. Computer Vision for Augmented Reality (Jan-Michael Frahm)
    7. 3D Camera Tracking, Reconstruction and View Synthesis at Interactive Frame Rates (Jan-Michael Frahm, Reinhard Koch, Jan-Friso Evers-Senne)
    8. Integration of Vision and Graphics, with Sports Applications part 1, part 2 (Oliver Grau)
    9. Improving Image Quality in Image Compositing (Mark Grundland)
    10. Open-source Insight Toolkit (ITK) for medical image segmentation and registration (Luis Ibanez, Lydia Ng, Joshua Cates, Stephen Aylward, Bill Lorensen, Julien Jomier)
    11. Face Detection and Recognition using Machine Learning (Sebastien Marcel)
    12. Face detection and recognition (Sebastien Marcel)
    13. Face Recognition (Sebastien Marcel)
    14. Computer Vision for Wearable Visual Interface (Walterio Mayol, Takeshi Kurata)
    15. Animate Vision concepts for image retrieval (Vincenzo Moscato)
    16. Spatio-temporal Data Mining (Shashi Shekhar)
    17. Multimedia Information Retrieval (Alan Smeaton)
    18. Multimedia Information Retrieval Evaluation Initiatives (Alan Smeaton)
    19. Designing multi-scale algorithms medical image analysis (Bart M. ter Haar Romeny)
    20. Biometrics for Surveillance (S. Kevin Zhou, Rama Chellappa)

Online Video Tutorials

  1. General
    1. Computational models of vision (Shimon Ullman, 1:30')
    2. Advanced Vision Course (Bob Fisher, 16:00)
    3. Computer Vision (Andrew Blake, 3:00)
    4. Applications to Machine Vision (Andrew Blake, 1:00)
    5. Computer vision (Richard Hartley, 3:00)
    6. Topics in image and video processing (Andrew Blake, 3:11')
    7. The Future of Image Search (Jitendra Malik, 1:00)
    8. Introduction to Vision and Robotics Course (Bob Fisher, ~8:00 video + 20:00 audio)
  2. Machine Learning in Computer Vision
    1. Learning in Computer Vision (Simon Lucey, 5:31')
    2. Machine learning and kernel methods for computer vision (Francis R. Bach, 0:40')
    3. Multiple kernel learning for multiple sources (Francis R. Bach, 0:45')
    4. Machine Learning in Vision (Bill Triggs, 2:40')
    5. Learning shared representations for object recognition (Antonio Torralba, 1:20')
    6. Learning Visual Distance Function for Object Identification from one Example (Frederic Jurie, 0:20')
    7. Energy-based models & Learning for Invariant Image Recognition (Yann LeCun, 3:40')
    8. Toward Learning Mixture-of-Parts Pictorial Structures (Alan Fern, 0:36')
    9. Enhancing functional magnetic resonance imaging with supervised learning (Stephen LaConte, 0:26')
    10. Learning with spectral representations and use of MDL principles (Edwin Hancock, 0:41' )
  3. Object Recognition
    1. Large-Scale Object Recognition Systems (Cordelia Schmid, 0:36')
    2. Global and Efficient Self-Similarity for Object Classification and Detection (Thomas Deselaers, 0:18')
    3. Object Recognition by Discriminative Combinations of Line Segments and Ellipses (Alex Chia, 0:18')
    4. Stereo Vision for Obstacle Detection: a Graph-Based Approach (Alessandro Limongiello, 0:40')
    5. 101 Visual object classes - Introduction (Andrew Zisserman, 0:52')
    6. Recognising Animals (Allan Hanbury, 0:20')
    7. Generative Models for Visual Objects and Object Recognition via Bayesian Inference (Fei-Fei Li, 01:00)
    8. Modeling Mutual Context of Object and Human Pose in Human-Object Interaction Activities (Fei-Fei Li, 0:19')
    9. Detecting Motifs Under Uniform Scaling (Dragomir Yankov, 0:18')
    10. Research 17: Integrating and Querying Parallel Leaf Shape Descriptions (Shenghui Wang, 0:28')
    11. Object Identification by Statistical Methods (Hans-Joachim Lenz, 1:22')
    12. Feature extraction & content description I (Nicu Sebe, 2:27')
    13. Feature extraction & content description II (Milind Naphade, 2:40')
    14. Understanding Visual Scenes (Antonio Torralba, 2:00)
    15. On Detection of Multiple Object Instances using Hough Transforms (Olga Barinova, 0:17')
    16. Grouplet: A Structured Image Representation for Recognizing Human and Object Interactions (Bangpeng Yao, 0:18')
    17. Food Recognition Using Statistics of Pairwise Local Features (Shulin (Lynn) Yang, 0:14')
    18. Multimodal semi-supervised learning for image classification (Matthieu Guillaumin, 0:19')
    19. Object-Graphs for Context-Aware Category Discovery (Yong Jae Lee, 0:18')
    20. Common Visual Pattern Discovery via Spatially Coherent Correspondences (Hairong Liu, 0:17')
    21. Cascade Object Detection with Deformable Part Models (Ross B. Girshick, 0:17')
    22. A Novel Riemannian Framework for Shape Analysis of 3D Objects (Sebastian Kurtek, 0:16')
  4. Segmentation
    1. Graph-Based Perceptual Segmentation of Stereo Vision 3D Images at Multiple Abstraction Levels (Rodrigo Moreno, 3:30')
    2. Adaptive Feature Selection in Image Segmentation (Volker Roth, 0:26')
    3. Object Recognition by Discriminative Combinations of Line Segments and Ellipses (Alex Chia, 0:18')
  5. Text Recognition
    1. Book-Adaptive and Book-Dependent Models to Accelerate Digitization of Early Music (Douglas Eck, 0:09')
    2. Text Recognition Evaluation (Padmanabhan Soundararajan, 0:16')
    3. Videotext Recognition System (Rahid Prasad, 0:17')
    4. Detecting Text in Natural Scenes with Stroke Width Transform (Boris Epshtein, 0:17')
    5. The chains model for detecting parts by their context (Leonid Karlinsky, 0:17')
  6. fMRI Analysis
    1. Multimodal Imaging: EEG-fMRI integration (Tom Eichele, 0:57')
    2. EEG/fMRI correlation analysis. A data and model driven approach (Jan de Munck, 1:00)
    3. Introduction and overview of FMRI concepts and terminology (John-Dylan Haynes, 0:27')
    4. Scanning the brain and probing the mind (Nigel Leigh, Blaz Koritnik, 1:31')
    5. Implications of decoding for theories of neural representation (James Haxby, 0:36')
    6. Exploring human object-vision with hi-res fMRI and information-based analysis (Nikolaus Kriegeskorte, 0:30')
    7. Hierarchical Gaussian Naive Bayes Classifier for Multiple-Subject fMRI Data (Indrayana Rustandi, 0:11')
    8. Overview of decoding of mental states and processes (Tom Mitchell, 0:25')
    9. Symbolic Dynamics of Neurophysiological Data (Peter beim Graben 0:50')
    10. Unsupervised fMRI Analysis (David R. Hardoon, 0:12')
    11. From functional elements to networks in fMRI (Ricardo Vigario, 0:52')
    12. Classifying single trial fMRI: What can machine learning learn? (Paul Mazaika, 0:12')
    13. fMRI-based decoding of the modified default-mode network in mild cognitive impairment (Fabian Theis, 0:15')
    14. Generative Models for Decoding Real-Valued Natural Experience in FMRI (Greg Stephens, 0:15')
  7. Motion and Tracking
    1. Visual localization and tracking (Andrew Blake, 3:00)
    2. Dynamical Binary Latent Variable Models for 3D Human Pose Tracking (Graham Taylo, 0:18')
    3. Projective Kalman Filter: Multiocular Tracking of 3D Locations Towards Scene Understanding (Cristian Ferrer Canton, 0:15')
    4. Visual Tracking Decomposition (Junseok Kwon, 0:18')
    5. Tracking the Invisible: Learning Where the Object Might Be (Helmut Grabner, 0:18')
  8. Other Subjects
    1. Qualitative Spatial Relationships for Image Interpretation by using Semantic Graph (Aline Deruyver, 0:20')
    2. Using computer vision in a rehabilitation method of a human hand (Jaka Katrasnik, 0:09')
    3. Large Scale Scene Matching for Graphics and Vision (James Hays, 01:00)
    4. Graph-based Methods for Retinal Mosaicing and Vascular Characterization (M. Elena Martinez-Perez, 0:30')
    5. Grouping Using Factor Graphs: an Approach for Finding Text with a Camera Phone (Huiying Shen, 0:22')
    6. Introduction to Multimedia Digital Libraries (James Wang, 3:00)
    7. Visual Categorization with Bags of Keypoints (Christopher Dance, 0:50')
    8. Spatiotemporal classification (Janaina Mourao-Miranda, 0:24')
    9. Image Classification Using Marginalized Kernels for Graphs (Emanuel Aldea, 0:20')
    10. Graph Cuts (Andrew Blake, ~1:00)
    11. Graph Cuts (Shorter) (Andrew Blake, ~0:30 )
    12. Probabilistic Relaxation Labeling by Fokker-Planck Diffusion on a Graph (Edwin Hancock, 0:21' )
    13. Graph Spectral Image Smoothing (Edwin Hancock, 0:28' )
    14. Videolectures->Computer Science->Computer Vision (videolectures.net)

Return to Student/Researcher Resource page


Valid XHTML 1.0!

© 2008 Robert Fisher