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3D model retrieval using accurate pose estimation and view-based similarity

Authors:

Apostolos Axenopoulos,

Georgios Litos,

Petros DarasAuthors Info & Claims

ICMR '11: Proceedings of the 1st ACM International Conference on Multimedia Retrieval

Article No.: 41, Pages 1 - 8

https://doi.org/10.1145/1991996.1992037

Published: 18 April 2011 Publication History

Abstract

In this paper, a novel framework for 3D object retrieval is presented. The paper focuses on the investigation of an accurate 3D model alignment method, which is achieved by combining two intuitive criteria, the plane reflection symmetry and rectilinearity. After proper positioning in a coordinate system, a set of 2D images (multi-views) are automatically generated from the 3D object, by taking views from uniformly distributed viewpoints. For each image, a set of flip-invariant shape descriptors is extracted. Taking advantage of both the pose estimation of the 3D objects and the flip-invariance property of the extracted descriptors, a new matching scheme for fast computation of 3D object dissimilarity is introduced. Experiments conducted in SHREC 2009 benchmark show the superiority of the pose estimation method over similar approaches, as well as the efficiency of the new matching scheme.

References

[1]

B. Bustos, D. Keim, D. Saupe, T. Schreck, "Contentbased 3d object retrieval", IEEE Computer Graphics and Applications 27 (4) pp. 22--27, 2007.

Digital Library

[2]

Kriegel, H.-P., Kroeger, P., Mashael, Z., Pfeifle, M., Poetke, M., & Seidl, T. (2003). Effective similarity search on voxelized cad objects. In Proc. of IEEE eighth international conference on database systems for advanced applications. Washington, DC, USA.

Digital Library

[3]

P. Daras, D. Zarpalas, D. Tzovaras, M. G. Strintzis, "Efficient 3-d model search and retrieval using generalized 3-d radon transforms", IEEE Transactions on Multimedia 8 (1), pp. 101114, 2006.

Digital Library

[4]

P. Papadakis, I. Pratikakis, S. Perantonis, T. Theoharis, "Efficient 3D shape matching and retrieval using a concrete radialized spherical projection representation", Pattern Recognition 40 (9), pp. 24372452, 2007.

Digital Library

[5]

A. Mademlis, P. Daras, A. Axenopoulos, D. Tzovaras, and M. G. Strintzis, "Combining Topological and Geometrical Features for Global and Partial 3D Shape Retrieval", IEEE Transactions on Multimedia, Volume 10, Issue 5, pp. 819--831, 2008.

Digital Library

[6]

R. Ohbuchi, K. Osada, T. Furuya and T. Banno, "Salient local visual features for shape-based 3D model retrieval", In Proc. og the IEEE International Conference on Shape Modeling and Applications, (SMI 2008), pp. 93--102, 2008.

[7]

P. Daras, A. Axenopoulos, "A 3D Shape Retrieval Framework Supporting Multimodal Queries", SPRINGER, International Journal of Computer Vision, DOI 10.1007/s11263-009-0277-2, Jul 2009.

Digital Library

[8]

C. Akgul, A. Axenopoulos, B. Bustos, M. Chaouch, P. Daras, H. Dutagaci, T. Furuya, A. Godil, S. Kreft, Z. Lian, T. Napoleon, A. Mademlis, R. Ohbuchi, P. L. Rosin, B. Sankur, T. Schreck, X. Sun, M. Tezuka, Y. Yemez, A. Verroust-Blondet, M. Walter, "SHREC 2009 - Generic Shape Retrieval Contest" 30th International conference on EUROGRAPHICS 2009, workshop on 3D object retrieval, Munich, Germany, Mar 2009.

Digital Library

[9]

Paquet, E., & Rioux, M. (1999). Nefertiti: a query by content system for three-dimensional model and image databases management. Image and Vision Computing, 17(2), 157--166.

[10]

Vrani'c, D. V., Saupe, D., & Richter, J. (2001). Tools for 3D-object retrieval: Karhunen-Loeve transform and spherical harmonics. In Proc. 2001 IEEE fourth workshop on multimedia signal processing (pp. 293--298).

[11]

Pu, J. T., and Ramani, K., "An Automatic Drawing-like View Generation Method from 3D Models", In Proceedings of ASME IDETC/CIE 2005, 25th Computers and Information in Engineering (CIE) Conference, Long Beach (USA), pp. 301--320, 2005

[12]

Z. Lian, P. L. Rosin, and X. Sun, "Rectilinearity of 3D meshes", International Journal of Computer Vision Volume 89, Numbers 2--3, 130--151.

Digital Library

[13]

Podolak J., Shilane P., Golovinskiy A., Rusinkiewicz S., Funkhouser T.: "A planar-reflective symmetry transform for 3D shapes", ACM Transactions on Graphics (Proc. SIGGRAPH) 25, 3 (July 2006).

Digital Library

[14]

Mohamed Chaouch, Anne Verroust-Blondet, "Alignment of 3D models", Graphical Models, v. 71 n. 2, p. 63--76, March, 2009.

Digital Library

[15]

"SHREC 2009 - Shape Retrieval Contest on a New Generic Shape Benchmark", http://www.itl.nist.gov/iad/vug/sharp/benchmark/shrecGeneric/index.htm

[16]

J. Kennedy and R. C. Eberhart (1995): Particle swarm optimization. Proc. IEEE Int. Conf. on Neural Networks, 4, 1942--1948. Piscataway, NJ: IEEE Service Center.

[17]

http://www.swarmintelligence.org/tutorials.php

[18]

P. Minovic, S. Ishikawa, K. Kato, Symmetry identification of a 3-D object represented by octree, IEEE Trans. Pattern Anal. Mach. Intell. 15 (5) (1993) 507--514.

Digital Library

[19]

C. Sun, J. Sherrah, 3D symmetry detection using the extended gaussian image, IEEE Trans. Pattern Anal. Mach. Intell. 19 (2) (1997) 164--168.

Digital Library

[20]

A. Martinet, C. Soler, N. Holzschuch, F. X. Sillion, Accurate detection of symmetries in 3D shapes, ACM Trans. Graphics 25 (2) (2006) 439--464.

Digital Library

[21]

M. Kazhdan, T. Funkhouser, S. Rusinkiewicz, Symmetry descriptors and 3D shape matching, in: Symposium on Geometry Processing, 2004.

Digital Library

Cited By

Sfikas KPratikakis ITheoharis T(2018)Ensemble of PANORAMA-based convolutional neural networks for 3D model classification and retrievalComputers & Graphics10.1016/j.cag.2017.12.00171(208-218)Online publication date: Apr-2018
https://doi.org/10.1016/j.cag.2017.12.001
Xie XLuo SZhang QFeng J(2017)A Hierarchical Symmetry Detection Algorithm Based on Voxelization2017 International Conference on Virtual Reality and Visualization (ICVRV)10.1109/ICVRV.2017.00025(85-90)Online publication date: Oct-2017
https://doi.org/10.1109/ICVRV.2017.00025
Xie XLuo SFeng J(2017)A general framework for 3D model co-alignmentComputer-Aided Design10.1016/j.cad.2017.05.00190:C(59-70)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.cad.2017.05.001
Show More Cited By

Index Terms

3D model retrieval using accurate pose estimation and view-based similarity
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Shape modeling

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICMR '11: Proceedings of the 1st ACM International Conference on Multimedia Retrieval

April 2011

512 pages

ISBN:9781450303361

DOI:10.1145/1991996

General Chairs:
Francesco G. B. De Natale
University of Trento, Italy
,
Alberto Del Bimbo
University of Florence, Italy
,
Program Chairs:
Alan Hanjalic
University of Amsterdam, Netherlands
,
B. S. Manjunath
University of California, Santa Barbara
,
Shin'ichi Satoh
NII, Japan

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 April 2011

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ICMR'11

Sponsor:

SIGMM

ICMR'11: International Conference on Multimedia Retrieval

April 18 - 20, 2011

Trento, Italy

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Overall Acceptance Rate 254 of 830 submissions, 31%

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Citations

Cited By

Sfikas KPratikakis ITheoharis T(2018)Ensemble of PANORAMA-based convolutional neural networks for 3D model classification and retrievalComputers & Graphics10.1016/j.cag.2017.12.00171(208-218)Online publication date: Apr-2018
https://doi.org/10.1016/j.cag.2017.12.001
Xie XLuo SZhang QFeng J(2017)A Hierarchical Symmetry Detection Algorithm Based on Voxelization2017 International Conference on Virtual Reality and Visualization (ICVRV)10.1109/ICVRV.2017.00025(85-90)Online publication date: Oct-2017
https://doi.org/10.1109/ICVRV.2017.00025
Xie XLuo SFeng J(2017)A general framework for 3D model co-alignmentComputer-Aided Design10.1016/j.cad.2017.05.00190:C(59-70)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.cad.2017.05.001
Sirin YDemirci M(2017)2D and 3D shape retrieval using skeleton filling rateMultimedia Tools and Applications10.1007/s11042-016-3422-276:6(7823-7848)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s11042-016-3422-2
Chen ZLin WTsai CKe S(2016)3D model retrieval by sample based alignmentJournal of Visual Communication and Image Representation10.1016/j.jvcir.2016.08.01740:PB(721-731)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.jvcir.2016.08.017
Li BLu YLi CGodil ASchreck TAono MBurtscher MChen QChowdhury NFang BFu HFuruya TLi HLiu JJohan HKosaka RKoyanagi HOhbuchi RTatsuma AWan YZhang CZou C(2015)A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queriesComputer Vision and Image Understanding10.1016/j.cviu.2014.10.006131:C(1-27)Online publication date: 1-Feb-2015
https://dl.acm.org/doi/10.1016/j.cviu.2014.10.006
Farrugia TBarbarar J(2015)Pose Normalisation for 3D VehiclesComputer Analysis of Images and Patterns10.1007/978-3-319-23192-1_20(235-245)Online publication date: 25-Aug-2015
https://doi.org/10.1007/978-3-319-23192-1_20
Sfikas KTheoharis TPratikakis I(2014)Pose normalization of 3D models via reflective symmetry on panoramic viewsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-014-0935-430:11(1261-1274)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1007/s00371-014-0935-4
Sfikas KPratikakis ITheoharis TCastellani USchreck TBiasotti SPratikakis I(2013)SymPanProceedings of the Sixth Eurographics Workshop on 3D Object Retrieval10.5555/2601307.2601314(41-48)Online publication date: 11-May-2013
https://dl.acm.org/doi/10.5555/2601307.2601314
Li BJohan H(2013)3D model retrieval using hybrid features and class informationMultimedia Tools and Applications10.1007/s11042-011-0873-362:3(821-846)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1007/s11042-011-0873-3
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