CVonline: Generic Vision Methods


  1. Accumulation/Voting Methods
    1. Hough
      1. Adaptive Hough Transform
      2. Analytic Curve Finding
      3. Cascaded Hough Transform
      4. Generalized Hough Transform
      5. Hierarchical Hough Transform
      6. Maximum Margin Hough Transform
      7. Performance Improvement Techniques
      8. Pose Estimation
      9. Probabilistic Hough Transform
      10. Randomised Hough Transform
      11. Surface Finding
      12. Velocity
    2. Tensor Voting
  2. Diffusion/PDE/Time-Based Evolution Methods
    1. Heat Kernel
  3. Eigenvector/Function Decompositions (See Eigenvector and Eigenfunction)
  4. Genetic Algorithms/Programming
  5. Graph Methods
    1. Graph Representations
      1. Adjacency Graph
      2. Association Graph
      3. Attributed Graph
      4. Dynamic Feature Graph
      5. Graph Embedding
      6. Hierarchical Graph/Hypergraph Representations
      7. Laplacian Smoothing
      8. Median Graph
      9. Optimal Basis Graphs
      10. Probabilistic Graph Representations
    2. Graph Matching
      1. Bayesian Graph Matching
      2. Bipartite Matching
      3. Graph Cuts
      4. Graph Kernel Methods
      5. Graph/Tree Edit Distance and Methods
      6. Maximal Cliques in Association Graphs
      7. Spectral Decomposition Methods
      8. Subgraph Isomorphism
    3. Multi-Dimensional Scaling
  6. Image Pyramids and Scale Reduction
    1. Adaptive Pyramids
    2. Gaussian Pyramids
    3. Laplacian Pyramids
  7. Level Sets
    1. Level Set Trees
  8. Minimum Description Length
  9. Multiple Scales/Resolutions
    1. Fractals
    2. Multi-Scale Integration
    3. Ranklets
    4. Scale Space
    5. Wavelets
      1. Noiselets
  10. Graph, Networks & Connectionist Methods
    1. Bayesian Networks
    2. Connectionist Methods
    3. Gaussian Process Methods (Regression, Classification0
    4. Neural Networks
    5. Probabilistic Graphical Models
      1. Expectation Propagation, Power Expectation Propagation Inference
      2. Fractional Belief Propagation Inference
      3. Loopy Belief Propagation Inference
      4. Message Passing, Tree Reweighted Message Passing, Variational Message Passing Inference
    6. Radial Basis Function Networks
    7. Wavelet Networks
  11. Regularization
  12. Relaxation
    1. Continuous
    2. Discrete
    3. Probabilistic/Stochastic
  13. Spatial Indexing/Spatial Hashing
  14. Subpixel Methods
  15. Super-resolution
  16. (Un)Certainty Representations
    1. Bayesian Networks (See Bayesian Networks)
    2. Discrete (See Relaxation)
    3. Fuzzy Logic
    4. Intervals
    5. Probabilities
  17. Vision Paradigms
    1. 3D Vision
    2. Active Vision (See Motion: Active Vision)
    3. Geometric Vision (See Vision Geometry and Mathematics and Geometric Representation of Model Features)
    4. Purposive Vision
    5. Qualitative Vision
  18. Vision System Design and Characterization
    1. Error Propagation
    2. Performance Characterization
    3. Receiver Operating Characteristics
    4. System Design Issues

Return to CVentry top level


Valid XHTML 1.0 Strict

© 2007 robert fisher