Interactive Image Segmentation Based on Hierarchical Graph-Cut Optimization with Generic Shape Prior
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
A Multi-Pronged Approach to Improving Semantic Extraction of News Video
Journal of Signal Processing Systems
Unconstrained face recognition using MRF priors and manifold traversing
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
MRF-based stereo correspondence and virtual view interpolation
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
A computer-aided detection system for clustered microcalcifications
Artificial Intelligence in Medicine
An extension of the standard mixture model for image segmentation
IEEE Transactions on Neural Networks
Implementing First-Order Variables in a Graphical Cognitive Architecture
Proceedings of the 2010 conference on Biologically Inspired Cognitive Architectures 2010: Proceedings of the First Annual Meeting of the BICA Society
Spatial regularization of functional connectivity using high-dimensional Markov random fields
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Discriminative fields for modeling semantic concepts in video
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Comparison of two algorithms for 3D skin reconstruction
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Spatio-temporal resolution enhancement of vocal tract MRI sequences based on image registration
Integrated Computer-Aided Engineering
Fast computation methods for estimation of image spatial entropy
Journal of Real-Time Image Processing
Topology-preserving registration: a solution via graph cuts
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Regression models for texture image analysis
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
A computationally efficient method for sequential MAP-MRF cloud detection
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II
Skeletonization of low-quality characters based on point cloud model
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part IV
The relevance voxel machine (RVoxM): A Bayesian method for image-based prediction
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Model based 3d segmentation and OCT image undistortion of percutaneous implants
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Dirichlet Gaussian mixture model: Application to image segmentation
Image and Vision Computing
Iterative Filtering Decomposition Based on Local Spectral Evolution Kernel
Journal of Scientific Computing
Mode Decomposition Evolution Equations
Journal of Scientific Computing
Recognition of dependent objects based on acyclic Markov models
Pattern Recognition and Image Analysis
Rethinking cognitive architecture via graphical models
Cognitive Systems Research
Semi-supervised clustering with discriminative random fields
Pattern Recognition
Modeling spatial dependencies and semantic concepts in data mining
Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications
Computational Statistics & Data Analysis
A unified approach to background adaptation and initialization in public scenes
Pattern Recognition
What genes tell about iris appearance
MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
A linear programming based method for joint object region matching and labeling
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Computer Vision and Image Understanding
Regularized discriminant entropy analysis
Pattern Recognition
A Comprehensive Survey to Face Hallucination
International Journal of Computer Vision
A homography transform based higher-order MRF model for stereo matching
Pattern Recognition Letters
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Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables systematic development of optimal vision algorithms when used with optimization principles. This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimisation. It treats various problems in low- and high-level computational vision in a systematic and unified way within the MAP-MRF framework. Among the main issues covered are: how to use MRFs to encode contextual constraints that are indispensable to image understanding; how to derive the objective function for the optimal solution to a problem; and how to design computational algorithms for finding an optimal solution. Easy-to-follow and coherent, the revised edition is accessible, includes the most recent advances, and has new and expanded sections on such topics as: Discriminative Random Fields (DRF) Strong Random Fields (SRF) Spatial-Temporal Models Total Variation Models Learning MRF for Classification (motivation + DRF) Relation to Graphic Models Graph Cuts Belief Propagation Features: Focuses on the application of Markov random fields to computer vision problems, such as image restoration and edge detection in the low-level domain, and object matching and recognition in the high-level domain Presents various vision models in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation Uses a variety of examples to illustrate how to convert a specific vision problem involving uncertainties and constraints into essentially an optimization problem under the MRF setting Introduces readers to the basic concepts, important models and various special classes of MRFs on the regular image lattice and MRFs on relational graphs derived from images Examines the problems of parameter estimation and function optimization Includes an extensive list of references This broad-ranging and comprehensive volume is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It has been class-tested and is suitable as a textbook for advanced courses relating to these areas.