ACM Home Page
Please provide us with feedback. Feedback
Topology matching for fully automatic similarity estimation of 3D shapes
Full text PdfPdf (463 KB)
Source International Conference on Computer Graphics and Interactive Techniques archive
Proceedings of the 28th annual conference on Computer graphics and interactive techniques table of contents
Pages: 203 - 212  
Year of Publication: 2001
ISBN:1-58113-374-X
Authors
Masaki Hilaga  The University of Tokyo
Yoshihisa Shinagawa  The University of Tokyo
Taku Kohmura  The Institute of Physical and Chemical Research
Tosiyasu L. Kunii  Hosei University and Kanazawa Institute of Technology
Sponsor
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 39,   Downloads (12 Months): 232,   Citation Count: 86
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/383259.383282
What is a DOI?

ABSTRACT

There is a growing need to be able to accurately and efficiently search visual data sets, and in particular, 3D shape data sets. This paper proposes a novel technique, called Topology Matching, in which similarity between polyhedral models is quickly, accurately, and automatically calculated by comparing Multiresolutional Reeb Graphs (MRGs). The MRG thus operates well as a search key for 3D shape data sets. In particular, the MRG represents the skeletal and topological structure of a 3D shape at various levels of resolution. The MRG is constructed using a continuous function on the 3D shape, which may preferably be a function of geodesic distance because this function is invariant to translation and rotation and is also robust against changes in connectivities caused by a mesh simplification or subdivision. The similarity calculation between 3D shapes is processed using a coarse-to-fine strategy while preserving the consistency of the graph structures, which results in establishing a correspondence between the parts of objects. The similarity calculation is fast and efficient because it is not necessary to determine the particular pose of a 3D shape, such as a rotation, in advance. Topology Matching is particularly useful for interactively searching for a 3D object because the results of the search fit human intuition well.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
M.de Berg and M.van Kreveld. Trekking in the Alps Without Freezing or Getting Tired. Algorithmica, Vol.18, pp.306-323, 1997.
 
2
 
3
 
4
H. Blum. A Transformation for Extracting New Descriptors of Shape. Proc. Symp. Models for the Perception of Speech and Visual Form, pp.362-380, MIT Press, 1967.
 
5
6
 
7
 
8
9
 
10
 
11
 
12
 
13
14
 
15
16
17
 
18
 
19
20
 
21
 
22
23
 
24
25
26
 
27
 
28
 
29
 
30
G. Reeb. Sur les points singuliers d'une forme de Pfaff completement integrable ou d'une fonction numerique {On the Singular Points of a Completely Integrable Pfaff Form or of a Numerical Function}. Comptes Randus Acad. Sciences Paris, Vol.222, pp.847-849, 1946.
 
31
 
32
 
33
 
34
35
36
37
 
38
 
39
 
40
 
41
Y. Zhou, A. Kaufman and A.W. Toga. Three-dimensional skeleton and centerline generation based on an approximate minimum distance field. The Visual Computer, Vol.14, No.7, pp.303-314, 1998.

CITED BY  86

Collaborative Colleagues:
Masaki Hilaga: colleagues
Yoshihisa Shinagawa: colleagues
Taku Kohmura: colleagues
Tosiyasu L. Kunii: colleagues