Persistent Heat Signature for Pose-oblivious Matching of Incomplete Models
Although understanding of shape features in the context of shape matching and retrieval has made considerable progress in recent years, the case for partial and incomplete models in presence of pose variations still begs a robust and efficient solution. A signature that encodes features at multi‐sca...
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| Vydáno v: | Computer graphics forum Ročník 29; číslo 5; s. 1545 - 1554 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Oxford, UK
Blackwell Publishing Ltd
01.07.2010
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | Although understanding of shape features in the context of shape matching and retrieval has made considerable progress in recent years, the case for partial and incomplete models in presence of pose variations still begs a robust and efficient solution. A signature that encodes features at multi‐scales in a pose invariant manner is more appropriate for this case. The Heat Kernel Signature function from spectral theory exhibits this multi‐scale property. We show how this concept can be merged with the persistent homology to design a novel efficient pose‐oblivious matching algorithm for all models, be they partial, incomplete, or complete. We make the algorithm scalable so that it can handle large data sets. Several test results show the robustness of our approach. |
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| AbstractList | AbstractAlthough understanding of shape features in the context of shape matching and retrieval has made considerable progress in recent years, the case for partial and incomplete models in presence of pose variations still begs a robust and efficient solution. A signature that encodes features at multi-scales in a pose invariant manner is more appropriate for this case. The Heat Kernel Signature function from spectral theory exhibits this multi-scale property. We show how this concept can be merged with the persistent homology to design a novel efficient pose-oblivious matching algorithm for all models, be they partial, incomplete, or complete. We make the algorithm scalable so that it can handle large data sets. Several test results show the robustness of our approach. Although understanding of shape features in the context of shape matching and retrieval has made considerable progress in recent years, the case for partial and incomplete models in presence of pose variations still begs a robust and efficient solution. A signature that encodes features at multi-scales in a pose invariant manner is more appropriate for this case. The Heat Kernel Signature function from spectral theory exhibits this multi-scale property. We show how this concept can be merged with the persistent homology to design a novel efficient pose-oblivious matching algorithm for all models, be they partial, incomplete, or complete. We make the algorithm scalable so that it can handle large data sets. Several test results show the robustness of our approach. |
| Author | Li, K. Ranjan, P. Wang, Y. Luo, C. Dey, T.K. Safa, I. |
| Author_xml | – sequence: 1 givenname: T.K. surname: Dey fullname: Dey, T.K. organization: The Ohio State University, Columbus OH, USA – sequence: 2 givenname: K. surname: Li fullname: Li, K. organization: The Ohio State University, Columbus OH, USA – sequence: 3 givenname: C. surname: Luo fullname: Luo, C. organization: The Ohio State University, Columbus OH, USA – sequence: 4 givenname: P. surname: Ranjan fullname: Ranjan, P. organization: The Ohio State University, Columbus OH, USA – sequence: 5 givenname: I. surname: Safa fullname: Safa, I. organization: The Ohio State University, Columbus OH, USA – sequence: 6 givenname: Y. surname: Wang fullname: Wang, Y. organization: The Ohio State University, Columbus OH, USA |
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| References_xml | – reference: Cohen-Steiner D., Edelsbrunner H., Harer J.: Extending persistence using poincaré and lefschetz duality. Foundations of Computational Mathematics 9, 1 (2009), 79-103. – reference: Chen D.-Y., Tian X. P., Shen Y.-T., Ouhyoung M.: On visual similarity based 3d model retrieval. Computer Graphics Forum 22, 3 (2003), 223-232. – reference: Siddiqi K., Zhang J., Macrini D., Shokoufandeh A., Bouix S., Dickinson S.: Retrieving articulated 3D models using medial surfaces. Machine Vision and Applications 19, 4 (2008), 261-274. – reference: Desbrun M., Meyer M., Schröder P., Barr A. H.: Implicit fairing of irregular meshes using diffusion and curvature flow. Computer Graphics 33, Annual Conference Series (1999), 317-324. – reference: Reuter M.: Hierarchical shape segmentation and registration via topological features of laplace-beltrami eigenfunctions. Internat. J. Computer Vision 89, 2 (2010), 287-308. – reference: Edelsbrunner H., Letscher D., Zomorodian A.: Topological persistence and simplification. Discrete Comput. Geom. 28 (2002), 511-533. – reference: Pinkall U., Polthier K.: Computing discrete minimal surfaces and their conjugates. Experimental Mathematics 2, 1 (1993), 15-36. – reference: Tangelder J. W., Veltkamp R. C: A survey of content based 3d shape retrieval methods. Multimedia Tools Appl. 39, 3 (2008), 441-471. – reference: Dodziuk J.: Finite-difference approach to the hodge theory of harmonic forms. American Journal of Mathematics 98, 1 (1978), 79-104. – reference: Zhang H., Sheffer A., Cohen-Or D., Zhou Q., Van Kaick O., Tagliasacchi A.: Deformation-drive shape correspondence. Computer Graphics Forum 27, 5 (2008), 1431-1439. – reference: Chen X., Golovinskiy A., Funkhouser T.: A benchmark for 3D mesh segmentation. ACM Transactions on Graphics (Proc. SIGGRAPH) 28, 3 (2009). – reference: Vallet B., LéAvy B.: Spectral geometry processing with manifold harmonics. Computer Graphics Forum (Proceedings Eurographics) 27 (2008), 251-260. – reference: Jain V., Zhang H.: A spectral approach to shape-based retrieval of articulated 3d models. Comput. Aided Des. 39, 5 (2007), 398-407. – reference: Sun J., Ovsjanikov M., Guibas L. J.: A concise and provably informative multi-scale signature based on heat diffusion. Comput. Graph. Forum 28, 5 (2009), 1383-1392. – reference: Chua C., Jarvis R.: Point signatures: A new representation for 3D object recognition. International Journal of Computer Vision 25, 1 (1996), 63-85. – reference: Reuter M., Wolter F.-E., Peinecke N.: Laplace-beltrami spectra as "shape-dna" of surfaces and solids. 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Forum – start-page: 1021 year: 2009 end-page: 1030 – volume: 27 start-page: 1431 issue: 5 year: 2008 end-page: 1439 article-title: Deformation‐drive shape correspondence publication-title: Computer Graphics Forum – volume: 38 start-page: 342 issue: 4 year: 2006 end-page: 366 article-title: Laplace‐beltrami spectra as “shape‐dna” of surfaces and solids publication-title: Computer-Aided Design – volume: 27 start-page: 251 year: 2008 end-page: 260 article-title: Spectral geometry processing with manifold harmonics publication-title: Computer Graphics Forum (Proceedings Eurographics) – start-page: 130 year: 2006 end-page: 150 – year: 2010 – start-page: 154 year: 2001 – start-page: 167 year: 2004 end-page: 178 – volume: 9 start-page: 79 issue: 1 year: 2009 end-page: 103 article-title: Extending persistence using poincaré and lefschetz duality publication-title: Foundations of Computational Mathematics – start-page: 119 year: 2006 end-page: 126 – volume: 25 start-page: 63 issue: 1 year: 1996 end-page: 85 article-title: Point signatures: A new representation for 3D object recognition publication-title: International Journal of Computer Vision – start-page: 278 year: 2008 end-page: 287 – year: 2002 – volume: 22 start-page: 223 issue: 3 year: 2003 end-page: 232 article-title: On visual similarity based 3d model retrieval publication-title: Computer Graphics Forum – year: 2006 – start-page: 131 year: 2006 end-page: 142 – volume: 89 start-page: 287 issue: 2 year: 2010 end-page: 308 article-title: Hierarchical shape segmentation and registration via topological features of laplace‐beltrami eigenfunctions publication-title: Internat. 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| Snippet | Although understanding of shape features in the context of shape matching and retrieval has made considerable progress in recent years, the case for partial... AbstractAlthough understanding of shape features in the context of shape matching and retrieval has made considerable progress in recent years, the case for... |
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| SubjectTerms | Algorithms and object representations Computer based modeling Computer graphics Geometry I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Curve I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Curve, surface, solid, and object representations I.3.8 [Computer Graphics]: Applications Invariants Kernels Matching Mathematical analysis Mathematical models Robustness Signatures solid Studies surface |
| Title | Persistent Heat Signature for Pose-oblivious Matching of Incomplete Models |
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| Volume | 29 |
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