ACM Transactions on Graphics (TOG)
Efficient compression and rendering of multi-resolution meshes
Proceedings of the conference on Visualization '02
Compression of Large 3D Engineering Models using Automatic Discovery of Repeating Geometric Features
VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
3D Model Retrieval with Spherical Harmonics and Moments
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Wavelet-Based Progressive Compression Scheme for Triangle Meshes: Wavemesh
IEEE Transactions on Visualization and Computer Graphics
Geometry-guided progressive lossless 3D mesh coding with octree (OT) decomposition
ACM SIGGRAPH 2005 Papers
3D Object Retrieval using Many-to-many Matching of Curve Skeletons
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
A planar-reflective symmetry transform for 3D shapes
ACM SIGGRAPH 2006 Papers
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
Graphical Models
Exploiting repeated patterns for efficient compression of massive models
Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry
Technologies for 3D mesh compression: A survey
Journal of Visual Communication and Image Representation
A GPU Based 3D Object Retrieval Approach Using Spatial Shape Information
ISM '10 Proceedings of the 2010 IEEE International Symposium on Multimedia
3D model alignment based on minimum projection area
The Visual Computer: International Journal of Computer Graphics - CGI'2011 Conference
Efficient 3-D model search and retrieval using generalized 3-D radon transforms
IEEE Transactions on Multimedia
3D object retrieval using an efficient and compact hybrid shape descriptor
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
A GPU based high-efficient and accurate optimal pose alignment approach of 3D objects
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
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This paper presents a new method that can largely compress massive models which consist of a wide range of connected components. Its effectiveness relies mainly on the number and the complexity of repeated components being found in the input model. Comparing with the state-of-the-art algorithm of 3D model compression based on the reuse of repeated components, our method can find more repeated components, both efficiently and precisely, so that high compression ratio is achieved with no further compression of the unique components and transformation matrices. By employing reflection-invariant transformation and other optimization means during the alignment preprocessing of 3D models, we solve some problems existing in previous methods simply, like PCA ambiguities. Especially thanks to the matching scheme based on voxelization, our method itself is robust when confronting the situation that covariance matrix of PCA is degenerated. Experimental results show that our method reduces considerably and stably the number of connected components in 3D models than the state-of-the-art algorithm so as to higher compression efficiency, and saves time around 20 times on average.