Stochastic simulation
Visual reconstruction
Robust regression and outlier detection
Robust regression and outlier detection
The theory and practice of Bayesian image labeling
International Journal of Computer Vision
A novel algorithm for color constancy
International Journal of Computer Vision
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Automatic symbolic traffic scene analysis using belief networks
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Markov random field modeling in computer vision
Markov random field modeling in computer vision
What can two images tell us about a third one?
International Journal of Computer Vision
Vehicle Segmentation and Classification Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
The Markov chain Monte Carlo method: an approach to approximate counting and integration
Approximation algorithms for NP-hard problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Updating of Projective and Affine Structure from Motion
International Journal of Computer Vision
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
3-D reconstruction of urban scenes from image sequences
Computer Vision and Image Understanding - Special issue on CAD-based computer vision
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
A Multibody Factorization Method for Independently Moving Objects
International Journal of Computer Vision
Complexity and information
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Is Machine Colour Constancy Good Enough?
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Factorization Methods for Projective Structure and Motion
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Stochastic Computation of Medial Axis in Markov Random Fields
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Object Localization by Bayesian Correlation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Robust Computation and Parametrization of Multiple View Relations
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Unified Factorization Algorithm for Points, Line Segments and Planes with Uncertainty Models
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Stochastic simulation algorithms for dynamic probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Hyperdynamics Importance Sampling
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Eyeglasses Removal from Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Commodity Real-time Stereo Vision for Navigation
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Parsing Images into Regions, Curves, and Curve Groups
International Journal of Computer Vision
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
Learning Outdoor Color Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A consensus sampling technique for fast and robust model fitting
Pattern Recognition
Fast mixing hyperdynamic sampling
Image and Vision Computing
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
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A standard method for handling Bayesian models is to use Markov chain Monte Carlo methods to draw samples from the posterior. We demonstrate this method on two core problems in computer vision—structure from motion and colour constancy. These examples illustrate a samplers producing useful representations for very large problems. We demonstrate that the sampled representations are trustworthy, using consistency checks in the experimental design. The sampling solution to structure from motion is strictly better than the factorisation approach, because: it reports uncertainty on structure and position measurements in a direct way; it can identify tracking errors; and its estimates of covariance in marginal point position are reliable. Our colour constancy solution is strictly better than competing approaches, because: it reports uncertainty on surface colour and illuminant measurements in a direct way; it incorporates all available constraints on surface reflectance and on illumination in a direct way; and it integrates a spatial model of reflectance and illumination distribution with a rendering model in a natural way. One advantage of a sampled representation is that it can be resampled to take into account other information. We demonstrate the effect of knowing that, in our colour constancy example, a surface viewed in two different images is in fact the same object. We conclude with a general discussion of the strengths and weaknesses of the sampling paradigm as a tool for computer vision.