Knowledge-based interpretation of outdoor natural color scenes
Knowledge-based interpretation of outdoor natural color scenes
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Bayesian Belief Networks as a tool for stochastic parsing
Speech Communication
Neural Computation
Statistical methods for automatic interpretation of digitally scanned finger prints
Pattern Recognition Letters - special issue on pattern recognition in practice V
Efficient multiresolution counterparts to variational methods for surface reconstruction
Computer Vision and Image Understanding
A revolution: belief propagation in graphs with cycles
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A non-parametric multi-scale statistical model for natural images
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A mean field learning algorithm for unsupervised neural networks
Learning in graphical models
Proceedings of the 1998 conference on Advances in neural information processing systems II
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Computer Vision
LOCO-I: a low complexity, context-based, lossless image compression algorithm
DCC '96 Proceedings of the Conference on Data Compression
Hidden Neural Networks: A Framework for HMM/NN Hybrids
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Hierarchical statistical models for the fusion of multiresolution image data
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
Multiresolution Gauss-Markov random field models for texture segmentation
IEEE Transactions on Image Processing
Discrete Markov image modeling and inference on the quadtree
IEEE Transactions on Image Processing
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Dynamic Trees: Learning to Model Outdoor Scenes
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Image Modeling with Position-Encoding Dynamic Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Neural Networks for Document Analysis and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence Review
Dynamic Trees for Unsupervised Segmentation and Matching of Image Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Interpretation of complex scenes using dynamic tree-structure Bayesian networks
Computer Vision and Image Understanding
Hierarchical Gaussian process latent variable models
Proceedings of the 24th international conference on Machine learning
Object boundary detection in images using a semantic ontology
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Image modeling using tree structured conditional random fields
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Labelfaces: parsing facial features by multiclass labeling with an epitome prior
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Multiscale conditional random fields for image labeling
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Man-made structure detection in natural images using a causal multiscale random field
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Dynamic background discrimination with a recurrent network
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
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We are concerned with the problem of image segmentation, in which each pixel is assigned to one of a predefined finite number of labels. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of label images. Following the work of, we consider the use of tree-structured belief networks (TSBNs) as prior models. The parameters in the TSBN are trained using a maximum-likelihood objective function with the EM algorithm and the resulting model is evaluated by calculating how efficiently it codes label images. A number of authors have used Gaussian mixture models to connect the label field to the image data. In this paper, we compare this approach to the scaled-likelihood method of where local predictions of pixel classification from neural networks are fused with the TSBN prior. Our results show a higher performance is obtained with the neural networks. We evaluate the classification results obtained and emphasize not only the maximum a posteriori segmentation, but also the uncertainty, as evidenced e.g., by the pixelwise posterior marginal entropies. We also investigate the use of conditional maximum-likelihood training for the TSBN and find that this gives rise to improved classification performance over the ML-trained TSBN.