Perceptual organization and the representation of natural form
Artificial Intelligence
Hands: a pattern theoretic study of biological shapes
Hands: a pattern theoretic study of biological shapes
Perceptual Organization for Scene Segmentation and Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
From volumes to views: an approach to 3-D object recognition
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Recognizing 3-D objects using 2-D images
Recognizing 3-D objects using 2-D images
Describing Complicated Objects by Implicit Polynomials
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
FORMS: a flexible object recognition and modeling system
International Journal of Computer Vision
Minimax entropy principle and its application to texture modeling
Neural Computation
Prior Learning and Gibbs Reaction-Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
The role of V1 in shape representation
CNS '96 Proceedings of the annual conference on Computational neuroscience : trends in research, 1997: trends in research, 1997
Stochastic Jump-Diffusion Process for Computing Medial Axes in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Stochastic Jump-Diffusion Process for Computing Medial Axes in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
Equivalence of Julesz Ensembles and FRAME Models
International Journal of Computer Vision - Special issue on Genomic Signal Processing
Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help?
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
Region Tracking via Level Set PDEs without Motion Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling Visual Patterns by Integrating Descriptive and Generative Methods
International Journal of Computer Vision
A Probabilistic Multi-scale Model for Contour Completion Based on Image Statistics
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Parsing Images into Region and Curve Processes
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Sketches with Curvature: The Curve Indicator Random Field and Markov Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation Given Partial Grouping Constraints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting Meaningful Curves from Images
Journal of Mathematical Imaging and Vision
An A Contrario Decision Method for Shape Element Recognition
International Journal of Computer Vision
Statistical Multi-Object Shape Models
International Journal of Computer Vision
A stochastic grammar of images
Foundations and Trends® in Computer Graphics and Vision
Learning Probabilistic Models for Contour Completion in Natural Images
International Journal of Computer Vision
The HCM for perceptual image segmentation
Neurocomputing
Perceptual Scale-Space and Its Applications
International Journal of Computer Vision
A Gibbsian Kohonen Network for Online Arabic Character Recognition
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
A Markov random field approach to multi-scale shape analysis
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Shape evolution driven by a perceptually motivated measure
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Generalizing edge detection to contour detection for image segmentation
Computer Vision and Image Understanding
A probabilistic grouping principle to go from pixels to visual structures
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Coupled shape distribution-based segmentation of multiple objects
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
The Gestalt heuristic: emerging abstraction to improve combinatorial search
Natural Computing: an international journal
Editor's choice article: On growth and formlets: Sparse multi-scale coding of planar shape
Image and Vision Computing
SLEDGE: Sequential Labeling of Image Edges for Boundary Detection
International Journal of Computer Vision
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The goal of this paper is to study a mathematical framework of 2D object shape modeling and learning for middle level vision problems, such as image segmentation and perceptual organization. For this purpose, we pursue generic shape models which characterize the most common features of 2D object shapes. In this paper, shape models are learned from observed natural shapes based on a minimax entropy learning theory [31], [32]. The learned shape models are Gibbs distributions defined on Markov random fields (MRFs). The neighborhood structures of these MRFs correspond to Gestalt laws驴colinearity, cocircularity, proximity, parallelism, and symmetry. Thus, both contour-based and region-based features are accounted for. Stochastic Markov chain Monte Carlo (MCMC) algorithms are proposed for learning and model verification. Furthermore, this paper provides a quantitative measure for the so-called nonaccidental statistics and, thus, justifies some empirical observations of Gestalt psychology by information theory. Our experiments also demonstrate that global shape properties can arise from interactions of local features.