Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Unsupervised segmentation of noisy and textured images using Markov random fields
CVGIP: Graphical Models and Image Processing
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
Building detection and description from a single intensity image
Computer Vision and Image Understanding
Automatic object extraction from aerial imagery—a survey focusing on buildings
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov random field modeling in image analysis
Markov random field modeling in image analysis
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Combining Belief Networks and Neural Networks for Scene Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Image Classification: City vs. Landscape
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Delineating buildings by grouping lines with MRFs
IEEE Transactions on Image Processing
International Journal of Computer Vision
Accelerated training of conditional random fields with stochastic gradient methods
ICML '06 Proceedings of the 23rd international conference on Machine learning
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
International Journal of Computer Vision
Hierarchical building recognition
Image and Vision Computing
Dynamic quantization for belief propagation in sparse spaces
Computer Vision and Image Understanding
Semi-supervised Edge Learning for Building Detection in Aerial Images
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Segmentation of Natural and Man-Made Structures by Independent Component Analysis
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Figure-ground segmentation using factor graphs
Image and Vision Computing
Cue Integration for Urban Area Extraction in Remote Sensing Images
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Contextual classification of image patches with latent aspect models
Journal on Image and Video Processing - Special issue on patches in vision
UAV global pose estimation by matching forward-looking aerial images with satellite images
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Natural scene classification using overcomplete ICA
Pattern Recognition
Active curve axis Gaussian mixture models
Pattern Recognition
Range segmentation of large building exteriors: A hierarchical robust approach
Computer Vision and Image Understanding
Large margin cost-sensitive learning of conditional random fields
Pattern Recognition
Learning conditional random fields for classification of hyperspectral images
IEEE Transactions on Image Processing
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
A Bayesian approach for scene interpretation with integrated hierarchical structure
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Inferring laser-scan matching uncertainty with conditional random fields
Robotics and Autonomous Systems
Probabilistic modeling for structural change inference
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Probabilistic cascade random fields for man-made structure detection
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Building detection with loosely-coupled hybrid feature descriptors
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Proceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications
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This paper presents a generative model based approach to man-made structure detection in 2D natural images. The proposed approach uses a causal multiscale random field suggested in [3] as a prior model on the class labels on the image sites. However, instead of assuming the conditional independence of the observed data, we propose to capture the local dependencies in the data using a multiscale feature vector. The distribution of the multiscale feature vectors is modeled as mixture of Gaussians. A set of robust multiscale features is presented that captures the general statistical properties of man-made structures at multiple scales without relying on explicit edge detection. The proposed approach was validated on real-world images from the Corel data set, and a performance comparison with other techniques is presented.