Themes

Posted on April 24th, 2008 by Tom

The following themes are meant to give an indication of topics of interest for the group. A more complete bibliography can be downloaded as a pdf.

This list is not meant to be prescriptive, but to act as a guide for choosing topics by potential presenters. If you have a suggestion for something that isn't on the list please contact Thoma Papadhimitri and we will add it. The scope includes well established topics (books and journals) as well as important new conference papers.

  • Computational photography/imaging/optics
    • Optics
    • Light field photography
    • Wavefront coding
    • Coded aperture imaging
    • Coded exposure imaging
    • Hybrid cameras
    • Compressive imaging
    • High Dynamic Range (HDR) imaging
  • Inverse Problems
    • Classical methods
    • Denoising
    • Blind Deconvolution (BD)
    • Superresolution (SR)
    • Multichannel BD/SR
    • Segmentation
    • Single image SR, interpolation
    • Inpainting, missing data, boundary conditions
    • Tomography
    • Registration & motion estimation
    • Spatially Varying (SV) restoration
    • Depth estmation/Depth from Defocus (DFD)
  • Image models
    • Markov Random Field (MRF) priors
    • Multiscale, multilevel, nonstationary MRF priors
    • Non-quadratic cost functionals
    • Total Variation (TV) models
    • Wavelet & filterbank models
    • Sampled & dictionary based priors
  • Optimisation & Simulation methods
    • MAP estimation, gradient descent, Alternating Minimisation
    • Conjugate gradients, preconditioning
    • EM algorithm
    • VB methods
    • Bayesian marginalisation methods
    • Markov chain Monte Carlo (MCMC) methods, MMSE estimates
    • Simulated annealing, genetic algorithms
    • Iterated Conditional Modes (ICM)
    • Graph cuts
    • Bounding functional, quadratic approximation methods
    • Sparse approximation methods
    • Dictionary learning
    • k-Nearest neighbour searches
    • PDEs
    • Belief propogation
    • Compressed sensing
    • Parallel processing and computational methods for optimisation
  • Classification
    • Neural networks
    • Support Vector Machines (SVMs)
    • AdaBoost
  • Tracking
  • Computer Vision & 3D reconstruction

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