 MRF tutorial |
| MCMC tutorial |
| MRF applications: Geman, S.
and Geman, D. (1984). ``Stochastic relaxation, Gibbs distribution and the
Bayesian restoration of images''. IEEE Transactions on Pattern Analysis
and Machine Intelligence, 6(6):721--741. |
| MRF applications: Frame: Filters, Random field And Maximum Entropy: --- Towards a Unified Theory for Texture Modeling, Song Chun Zhu, Ying Nian Wu and David Mumford, Int'l Journal of Computer Vision 27(2) 1-20, March/April. 1998. |
|
S.C. Zhu, Embedding Gestalt Laws in Markov Random Fields, PAMI Nov. 99
PAMI June 2000, Exploring texture ensembles by efficient MCMC |
| M.C. Burl, M. Weber and P. Perona, A probabilistic approach to object recognition using local photometry & global geometry, Proc. of the 5th European Conf. on Computer Vision, ECCV 98. |
| Viola, Complex feature recognition: a bayesian approach for learning to recognize objects |
| Srivastava, etc. Ergodic algorithms on special Euclidean groups for
ATR
PAMI July 2000, Dominant-Subspace Invariants
|
| Sato & Cipolla. Affine reconstruction of curved surfaces from unclaibrated views of apparent contours. |
| RANSAC: Torr, robust estimation of fundamental matrix
PAMI June 2000, Fast and globally converegnt pose estimation from video images. (Estimating 2-D pose from 3-D) PAMI July 2000, A new SFM ambiguity |
| Paragios & Deriche. Geodesic active contours and level sets for the detection and tracking of objects. PAMI Vol. 22, No. 3, 2000. |
| Yuille & Coughlan. Fundamental limits of Beaysian inference.
PAMI. Vol. 22. No. 2. February. 2000
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
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