Free-form deformation of solid geometric models
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
On active contour models and balloons
CVGIP: Image Understanding
Unsupervised Texture Segmentation Using Markov Random Field Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary Finding with Parametrically Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Matching Distance Functions: A Shape-to-Area Variational Approach for Global-to-Local Registration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Texture segmentation using filters with optimized energy separation
IEEE Transactions on Image Processing
Wavelet-based level set evolution for classification of textured images
IEEE Transactions on Image Processing
CoCRF deformable model: a geometric model driven by collaborative conditional random fields
IEEE Transactions on Image Processing
Deformable probability maps: Probabilistic shape and appearance-based object segmentation
Computer Vision and Image Understanding
Automatic detection and segmentation of ground glass opacity nodules
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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In this paper, we present a deformable-model based solution for segmenting objects with complex texture patterns of all scales. The external image forces in traditional deformable models come primarily from edges or gradient information and it becomes problematic when the object surfaces have complex large-scale texture patterns that generate many local edges within a same region. We introduce a new textured object segmentation algorithm that has both the robustness of model-based approaches and the ability to deal with non-uniform textures of both small and large scales. The main contributions include an information-theoretical approach for computing the natural scale of a “texon” based on model-interior texture, a nonparametric texture statistics comparison technique and the determination of object belongingness through belief propagation. Another important property of the proposed algorithm is in that the texture statistics of an object of interest are learned online from evolving model interiors, requiring no other a priori information. We demonstrate the potential of this model-based framework for texture learning and segmentation using both natural and medical images with various textures of all scales and patterns.