Energy minimization methods in computer vision and pattern recognition : Second International Workshop EMMCVPR '99, York, UK, July 26-29, 1999 : proceedings
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書誌事項
Energy minimization methods in computer vision and pattern recognition : Second International Workshop EMMCVPR '99, York, UK, July 26-29, 1999 : proceedings
（Lecture notes in computer science, 1654）
Springer, c1999
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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目次
Shape.- A Hamiltonian Approach to the Eikonal Equation.- Topographic Surface Structure from 2D Images Using Shape-from-Shading.- Harmonic Shape Images: A Representation for 3D Free-Form Surfaces Based on Energy Minimization.- Deformation Energy for Size Functions.- Minimum Description Length.- On Fitting Mixture Models.- Bayesian Models for Finding and Grouping Junctions.- Markov Random Fields.- Semi-iterative Inferences with Hierarchical Energy-Based Models for Image Analysis.- Metropolis vs Kawasaki Dynamic for Image Segmentation Based on Gibbs Models.- Hyperparameter Estimation for Satellite Image Restoration by a MCMCML Method.- Auxiliary Variables for Markov Random Fields with Higher Order Interactions.- Unsupervised Multispectral Image Segmentation Using Generalized Gaussian Noise Model.- Contours.- Adaptive Bayesian Contour Estimation: A Vector Space Representation Approach.- Adaptive Pixel-Based Data Fusion for Boundary Detection.- Search and Consistent Labeling.- Bayesian A* Tree Search with Expected O(N) Convergence Rates for Road Tracking.- A New Algorithm for Energy Minimization with Discontinuities.- Convergence of a Hill Climbing Genetic Algorithm for Graph Matching.- A New Distance Measure for Non-rigid Image Matching.- Continuous-Time Relaxation Labeling Processes.- Tracking and Video.- Realistic Animation Using Extended Adaptive Mesh for Model Based Coding.- Maximum Likelihood Inference of 3D Structure from Image Sequences.- Biomedical Applications.- Magnetic Resonance Imaging Based Correction and Reconstruction of Positron Emission Tomography Images.- Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm4.
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