ACM Transactions on Graphics (TOG)
Quantitative methods of evaluating image segmentation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Hierarchical mesh segmentation based on fitting primitives
The Visual Computer: International Journal of Computer Graphics
Mesh Segmentation - A Comparative Study
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
SnapPaste: an interactive technique for easy mesh composition
The Visual Computer: International Journal of Computer Graphics
Consistent mesh partitioning and skeletonisation using the shape diameter function
The Visual Computer: International Journal of Computer Graphics
Fast mesh segmentation using random walks
Proceedings of the 2008 ACM symposium on Solid and physical modeling
Randomized cuts for 3D mesh analysis
ACM SIGGRAPH Asia 2008 papers
Hierarchical aggregation for efficient shape extraction
The Visual Computer: International Journal of Computer Graphics
A benchmark for 3D mesh segmentation
ACM SIGGRAPH 2009 papers
Interactive part selection for mesh and point models using hierarchical graph-cut partitioning
Proceedings of Graphics Interface 2009
A hierarchical segmentation of articulated bodies
SGP '08 Proceedings of the Symposium on Geometry Processing
Learning 3D mesh segmentation and labeling
ACM SIGGRAPH 2010 papers
A comparative study of existing metrics for 3D-mesh segmentation evaluation
The Visual Computer: International Journal of Computer Graphics
Interactive Mesh Cutting Using Constrained Random Walks
IEEE Transactions on Visualization and Computer Graphics
Semi-supervised segmentation of 3D surfaces using a weighted graph representation
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Joint shape segmentation with linear programming
Proceedings of the 2011 SIGGRAPH Asia Conference
Unsupervised co-segmentation of a set of shapes via descriptor-space spectral clustering
Proceedings of the 2011 SIGGRAPH Asia Conference
Variational mesh decomposition
ACM Transactions on Graphics (TOG)
Mesh Segmentation with Concavity-Aware Fields
IEEE Transactions on Visualization and Computer Graphics
Dot Scissor: A Single-Click Interface for Mesh Segmentation
IEEE Transactions on Visualization and Computer Graphics
Co-Segmentation of 3D Shapes via Subspace Clustering
Computer Graphics Forum
Active co-analysis of a set of shapes
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Unsupervised co-segmentation for 3D shapes using iterative multi-label optimization
Computer-Aided Design
Semi-supervised Mesh Segmentation and Labeling
Computer Graphics Forum
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3D model segmentation avails to skeleton extraction, shape partial matching, shape correspondence, texture mapping, shape deformation, and shape annotation. Many excellent solutions have been proposed in the last decade. How to efficiently evaluate these methods and impartially compare their performances are important issues. Since the Princeton segmentation benchmark has been proposed, their four representative metrics have been extensively adopted to evaluate segmentation algorithms. However, comparison to only a fixed ground-truth is problematic because objects have many semantic segmentations, hence we propose two novel metrics to support comparison with multiple ground-truth segmentations, which are named Similarity Hamming Distance (SHD) and Adaptive Entropy Increment (AEI). SHD is based on partial similarity correspondences between automatic segmentation and ground-truth segmentations, and AEI measures entropy change when an automatic segmentation is added to a set of different ground-truth segmentations. A group of experiments demonstrates that the metrics are able to provide relatively higher discriminative power and stability when evaluating different hierarchical segmentations, and also provide an effective evaluation more consistent with human perception.