Diffusions for global optimizations
SIAM Journal on Control and Optimization
Segmentation and Classification of Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
An optimization-based approach to the interpretation of single line drawings as 3D wire frames
International Journal of Computer Vision
Segmentation of 3D range images using pyramidal data structures
CVGIP: Image Understanding
A Bayesian multiple-hypothesis approach to edge grouping and contour segmentation
International Journal of Computer Vision
Segmentation of range images as the search for geometric parametric models
International Journal of Computer Vision
An Experimental Comparison of Range Image Segmentation Algorithms
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
International Journal of Computer Vision
Model selection techniques and merging rules for range data segmentation algorithms
Computer Vision and Image Understanding
Robust Segmentation of Primitives from Range Data in the Presence of Geometric Degeneracy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Data-Driven Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Filtering, Segmentation, and Depth
Filtering, Segmentation, and Depth
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction of Planar Surfaces Behind Occlusions in Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometry and texture recovery of scenes of large scale
Computer Vision and Image Understanding
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Comparing Curved-Surface Range Image Segmenters
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Graph Partition by Swendsen-Wang Cuts
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Consistency of robust estimators in multi-structural visual data segmentation
Pattern Recognition
Extraction of Geometrical Features in 3D Environments for Service Robotic Applications
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
A Geometric Primitive Extraction Process for Remote Sensing Problems
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
A Simple Sample Consensus Algorithm to Find Multiple Models
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Range segmentation of large building exteriors: A hierarchical robust approach
Computer Vision and Image Understanding
Range and intensity vision for rock-scene segmentation
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
IEEE Transactions on Image Processing
Line maps in cluttered environments
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Complex and photo-realistic scene representation based on range planar segmentation and model fusion
International Journal of Robotics Research
Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
International Journal of Computer Vision
Abstraction and depiction of sparsely scanned outdoor environments
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Efficient monte carlo sampler for detecting parametric objects in large scenes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Detecting parametric objects in large scenes by Monte Carlo sampling
International Journal of Computer Vision
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This paper presents an effective jump-diffusion method for segmenting a range image and its associated reflectance image in the Bayesian framework. The algorithm works on complex real-world scenes (indoor and outdoor), which consist of an unknown number of objects (or surfaces) of various sizes and types, such as planes, conics, smooth surfaces, and cluttered objects (like trees and bushes). Formulated in the Bayesian framework, the posterior probability is distributed over a solution space with a countable number of subspaces of varying dimensions. The algorithm simulates Markov chains with both reversible jumps and stochastic diffusions to traverse the solution space. The reversible jumps realize the moves between subspaces of different dimensions, such as switching surface models and changing the number of objects. The stochastic Langevin equation realizes diffusions within each subspace. To achieve effective computation, the algorithm precomputes some importance proposal probabilities over multiple scales through Hough transforms, edge detection, and data clustering. The latter are used by the Markov chains for fast mixing. The algorithm is tested on 100 1D simulated data sets for performance analysis on both accuracy and speed. Then, the algorithm is applied to three data sets of range images under the same parameter setting. The results are satisfactory in comparison with manual segmentations.