Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Solid shape
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Partitioning 3D Surface Meshes Using Watershed Segmentation
IEEE Transactions on Visualization and Computer Graphics
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Decomposing Polygon Meshes by Means of Critical Points
MMM '04 Proceedings of the 10th International Multimedia Modelling Conference
Feature Sensitive Mesh Segmentation with Mean Shift
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
Hierarchical mesh segmentation based on fitting primitives
The Visual Computer: International Journal of Computer Graphics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Neural Networks
Consistent mesh partitioning and skeletonisation using the shape diameter function
The Visual Computer: International Journal of Computer Graphics
A benchmark for 3D mesh segmentation
ACM SIGGRAPH 2009 papers
Surface mesh segmentation and smooth surface extraction through region growing
Computer Aided Geometric Design
A new CAD mesh segmentation method, based on curvature tensor analysis
Computer-Aided Design
3D mesh segmentation using mean-shifted curvature
GMP'08 Proceedings of the 5th international conference on Advances in geometric modeling and processing
Feature-preserving mesh denoising based on vertices classification
Computer Aided Geometric Design
GlobFit: consistently fitting primitives by discovering global relations
ACM SIGGRAPH 2011 papers
Automatic extraction of surface structures in digital shape reconstruction
GMP'06 Proceedings of the 4th international conference on Geometric Modeling and Processing
Fast and Effective Feature-Preserving Mesh Denoising
IEEE Transactions on Visualization and Computer Graphics
Surface mesh denoising with normal tensor framework
Graphical Models
Least squares quantization in PCM
IEEE Transactions on Information Theory
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In order to robustly perform segmentation for industrial design objects measured by a 3-D scanning device, we propose a new method for high-quality vertex clustering on a noisy mesh. Using Student-tmixture model with the variational Bayes approximation, we develop a vertex clustering algorithm in the 9-D space composed of three kinds of principal curvature measures along with vertex position and normal component. The normal component is added, because it well describes the surface-features and is less influenced by noise, and the positional component suppresses redundant clusters due to the normal one. Furthermore, in order to enhance the robustness for noisy data, considering mesh topology as a spatial constraint and letting the vertices in its surroundings belong to the same cluster by diffusion process, we protect generating many small fragments due to noise. We demonstrate effectiveness of our method by applying it to the real-world scanned data.