Decomposing linear and affine transformations
Graphics Gems III
Hierarchical mesh decomposition using fuzzy clustering and cuts
ACM SIGGRAPH 2003 Papers
Polynomial-Time Metrics for Attributed Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Hierarchical Models of Scenes, Objects, and Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Hierarchical mesh segmentation based on fitting primitives
The Visual Computer: International Journal of Computer Graphics
Perception Strategies in Hierarchical Vision Systems
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Model Composition from Interchangeable Components
PG '07 Proceedings of the 15th Pacific Conference on Computer Graphics and Applications
Randomized cuts for 3D mesh analysis
ACM SIGGRAPH Asia 2008 papers
A benchmark for 3D mesh segmentation
ACM SIGGRAPH 2009 papers
Technical Section: Consistent segmentation of 3D models
Computers and Graphics
Multi-instance clustering with applications to multi-instance prediction
Applied Intelligence
A hierarchical segmentation of articulated bodies
SGP '08 Proceedings of the Symposium on Geometry Processing
Illustrating how mechanical assemblies work
ACM SIGGRAPH 2010 papers
Learning 3D mesh segmentation and labeling
ACM SIGGRAPH 2010 papers
Contextual Part Analogies in 3D Objects
International Journal of Computer Vision
Style-content separation by anisotropic part scales
ACM SIGGRAPH Asia 2010 papers
Research frontier: deep machine learning--a new frontier in artificial intelligence research
IEEE Computational Intelligence Magazine
Exploration of continuous variability in collections of 3D shapes
ACM SIGGRAPH 2011 papers
Characterizing structural relationships in scenes using graph kernels
ACM SIGGRAPH 2011 papers
Probabilistic reasoning for assembly-based 3D modeling
ACM SIGGRAPH 2011 papers
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
A probabilistic model for component-based shape synthesis
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Fit and diverse: set evolution for inspiring 3D shape galleries
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Exploring Shape Variations by 3D-Model Decomposition and Part-based Recombination
Computer Graphics Forum
Acquiring 3D indoor environments with variability and repetition
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Active co-analysis of a set of shapes
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Co-abstraction of shape collections
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
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We introduce an unsupervised co-hierarchical analysis of a set of shapes, aimed at discovering their hierarchical part structures and revealing relations between geometrically dissimilar yet functionally equivalent shape parts across the set. The core problem is that of representative co-selection. For each shape in the set, one representative hierarchy (tree) is selected from among many possible interpretations of the hierarchical structure of the shape. Collectively, the selected tree representatives maximize the within-cluster structural similarity among them. We develop an iterative algorithm for representative co-selection. At each step, a novel cluster-and-select scheme is applied to a set of candidate trees for all the shapes. The tree-to-tree distance for clustering caters to structural shape analysis by focusing on spatial arrangement of shape parts, rather than their geometric details. The final set of representative trees are unified to form a structural co-hierarchy. We demonstrate co-hierarchical analysis on families of man-made shapes exhibiting high degrees of geometric and finer-scale structural variabilities.