Efficient Interpolation of Articulated Shapes Using Mixed Shape Spaces
Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to fin...
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| Veröffentlicht in: | Computer graphics forum Jg. 32; H. 8; S. 258 - 270 |
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01.12.2013
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state‐of‐the‐art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non‐rigid joints. This allows us to use fast vertex interpolation on the rigid parts and resort to comparatively slow edge‐based interpolation only for the joints.
Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state‐of‐the‐art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non‐rigid joints. |
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| AbstractList | Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state-of-the-art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non-rigid joints. This allows us to use fast vertex interpolation on the rigid parts and resort to comparatively slow edge-based interpolation only for the joints. [PUBLICATION ABSTRACT] Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state-of-the-art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non-rigid joints. This allows us to use fast vertex interpolation on the rigid parts and resort to comparatively slow edge-based interpolation only for the joints. Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state-of-the-art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non-rigid joints. Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state‐of‐the‐art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non‐rigid joints. This allows us to use fast vertex interpolation on the rigid parts and resort to comparatively slow edge‐based interpolation only for the joints. Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state‐of‐the‐art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non‐rigid joints. This allows us to use fast vertex interpolation on the rigid parts and resort to comparatively slow edge‐based interpolation only for the joints. Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state‐of‐the‐art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non‐rigid joints. |
| Author | Cashman, T. J. Hormann, K. Marras, S. |
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| References | [YYPM11] Yang Y.-L., Yang Y.-J., Pottmann H., Mitra N. J.: Shape space exploration of constrained meshes. ACM Transactions on Graphics 30, 6 (2011), #124:1-12. [FB11] Fröhlich S., Botsch M.: Example-driven deformations based on discrete shells. Computer Graphics Forum 30, 8 (2011), 2246-2257. [WDAH10] Winkler T., Drieseberg J., Alexa M., Hormann K.: Multi-scale geometry interpolation. Computer Graphics Forum 29, 2 (2010), 309-318. [KG08] Kircher S., Garland M.: Free-form motion processing. ACM Transactions on Graphics 27, 2 (2008), #12:1-13. [CH12] Cashman T. J., Hormann K.: A continuous, editable representation for deforming mesh sequences with separate signals for time, pose and shape. Computer Graphics Forum 31, 2 (2012), 735-744. [MBH*12] Marras S., Bronstein M. M., Hormann K., Scateni R., Scopogno R.: Motion-based mesh segmentation using augmented silhouettes. Graphical Models 74, 4 (2012), 164-172. [Sha08] Shamir A.: A survey on mesh segmentation techniques. Computer Graphics Forum 27, 6 (2008), 1539-1556. [SZT*08] Shi X., Zhou K., Tong Y., Desbrun M., Bao H., Guo B.: Example-based dynamic skinning in real time. ACM Transactions on Graphics 27, 3 (2008), #29:1-8. [KMP07] Kilian M., Mitra N. J., Pottmann H.: Geometric modeling in shape space. ACM Transactions on Graphics 26, 3 (2007), #64:1-8. [CDHR08] Chen Y., Davis T. A., Hager W. W., Rajamanickam S.: Algorithm 887: CHOLMOD, supernodal sparse cholesky factorization and update/downdate. ACM Transactions on Mathematical Software 35, 3 (2008), 2201-2214. [BB11] Bronstein M. M., Bronstein A. M.: Shape recognition with spectral distances. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 5 (2011), 1065-1071. [WB10] Wuhrer S., Brunton A.: Segmenting animated objects into near-rigid components. The Visual Computer 26, 2 (2010), 147-155. [HRWW12] Heeren B., Rumpf M., Wardetzky M., Wirth B.: Time-discrete geodesics in the space of shells. Computer Graphics Forum 31, 5 (2012), 1755-1764. [LSLCO05] Lipman Y., Sorkine O., Levin D., Cohen-Or, D.: Linear rotation-invariant coordinates for meshes. ACM Transactions on Graphics 24, 3 (2005), 479-487. [CLL*05] Coifman R. R., Lafon S., Lee A. B., Maggioni M., Nadler B., Warner F., Zucker S. W.: Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps. Proceedings of the National Academy of Sciences USA 102, 21 (2005), 7426-7431. [BVGP09] Baran I., Vlasic D., Grinspun E., Popović, J.: Semantic deformation transfer. ACM Transactions on Graphics (TOG) 28, 3 (2009), #36:1-6. [SP04] Sumner R. W., Popović, J.: Deformation transfer for triangle meshes. ACM Transactions on Graphics 23, 3 (2004), 399-405. [JT05] James D. L., Twigg C. D.: Skinning mesh animations. ACM Transactions on Graphics 24, 3 (2005), 399-407. [KP11] Kim J., Pollard N. S.: Fast simulation of skeleton-driven deformable body characters. ACM Transactions on Graphics 30, 5 (2011), #121:1-19. 2010; 26 2000 2010 2010; 29 2005; 102 2008; 27 2004; 23 2011; 30 2011; 33 2008; 35 2005 2003 2012; 31 2005; 24 2007; 26 2012; 74 2009; 28 e_1_2_6_21_1 e_1_2_6_20_1 e_1_2_6_9_1 e_1_2_6_8_1 e_1_2_6_19_1 e_1_2_6_5_1 e_1_2_6_4_1 e_1_2_6_7_1 e_1_2_6_6_1 e_1_2_6_13_1 e_1_2_6_25_1 e_1_2_6_14_1 Williams J. A. (e_1_2_6_22_1) 2000 e_1_2_6_24_1 e_1_2_6_3_1 e_1_2_6_11_1 e_1_2_6_23_1 e_1_2_6_2_1 Grinspun E. (e_1_2_6_10_1) 2003 e_1_2_6_12_1 e_1_2_6_17_1 e_1_2_6_18_1 e_1_2_6_15_1 e_1_2_6_16_1 |
| References_xml | – reference: [Sha08] Shamir A.: A survey on mesh segmentation techniques. Computer Graphics Forum 27, 6 (2008), 1539-1556. – reference: [YYPM11] Yang Y.-L., Yang Y.-J., Pottmann H., Mitra N. J.: Shape space exploration of constrained meshes. ACM Transactions on Graphics 30, 6 (2011), #124:1-12. – reference: [WB10] Wuhrer S., Brunton A.: Segmenting animated objects into near-rigid components. The Visual Computer 26, 2 (2010), 147-155. – reference: [BVGP09] Baran I., Vlasic D., Grinspun E., Popović, J.: Semantic deformation transfer. ACM Transactions on Graphics (TOG) 28, 3 (2009), #36:1-6. – reference: [JT05] James D. L., Twigg C. D.: Skinning mesh animations. ACM Transactions on Graphics 24, 3 (2005), 399-407. – reference: [MBH*12] Marras S., Bronstein M. M., Hormann K., Scateni R., Scopogno R.: Motion-based mesh segmentation using augmented silhouettes. Graphical Models 74, 4 (2012), 164-172. – reference: [LSLCO05] Lipman Y., Sorkine O., Levin D., Cohen-Or, D.: Linear rotation-invariant coordinates for meshes. ACM Transactions on Graphics 24, 3 (2005), 479-487. – reference: [CLL*05] Coifman R. R., Lafon S., Lee A. B., Maggioni M., Nadler B., Warner F., Zucker S. W.: Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps. Proceedings of the National Academy of Sciences USA 102, 21 (2005), 7426-7431. – reference: [SZT*08] Shi X., Zhou K., Tong Y., Desbrun M., Bao H., Guo B.: Example-based dynamic skinning in real time. ACM Transactions on Graphics 27, 3 (2008), #29:1-8. – reference: [KG08] Kircher S., Garland M.: Free-form motion processing. ACM Transactions on Graphics 27, 2 (2008), #12:1-13. – reference: [BB11] Bronstein M. M., Bronstein A. M.: Shape recognition with spectral distances. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 5 (2011), 1065-1071. – reference: [HRWW12] Heeren B., Rumpf M., Wardetzky M., Wirth B.: Time-discrete geodesics in the space of shells. Computer Graphics Forum 31, 5 (2012), 1755-1764. – reference: [SP04] Sumner R. W., Popović, J.: Deformation transfer for triangle meshes. ACM Transactions on Graphics 23, 3 (2004), 399-405. – reference: [FB11] Fröhlich S., Botsch M.: Example-driven deformations based on discrete shells. Computer Graphics Forum 30, 8 (2011), 2246-2257. – reference: [CDHR08] Chen Y., Davis T. A., Hager W. W., Rajamanickam S.: Algorithm 887: CHOLMOD, supernodal sparse cholesky factorization and update/downdate. ACM Transactions on Mathematical Software 35, 3 (2008), 2201-2214. – reference: [WDAH10] Winkler T., Drieseberg J., Alexa M., Hormann K.: Multi-scale geometry interpolation. Computer Graphics Forum 29, 2 (2010), 309-318. – reference: [CH12] Cashman T. J., Hormann K.: A continuous, editable representation for deforming mesh sequences with separate signals for time, pose and shape. Computer Graphics Forum 31, 2 (2012), 735-744. – reference: [KP11] Kim J., Pollard N. S.: Fast simulation of skeleton-driven deformable body characters. ACM Transactions on Graphics 30, 5 (2011), #121:1-19. – reference: [KMP07] Kilian M., Mitra N. J., Pottmann H.: Geometric modeling in shape space. ACM Transactions on Graphics 26, 3 (2007), #64:1-8. – volume: 74 start-page: 164 issue: 4 year: 2012 end-page: 172 article-title: Motion‐based mesh segmentation using augmented silhouettes publication-title: Graphical Models – start-page: 62 year: 2003 end-page: 67 – volume: 30 start-page: 2246 issue: 8 year: 2011 end-page: 2257 article-title: Example‐driven deformations based on discrete shells publication-title: Computer Graphics Forum – volume: 27 start-page: 1 issue: 2 year: 2008 end-page: 13 article-title: Free‐form motion processing publication-title: ACM Transactions on Graphics – volume: 102 start-page: 7426 issue: 21 year: 2005 end-page: 7431 article-title: Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps publication-title: Proceedings of the National Academy of Sciences USA – volume: 30 start-page: 1 issue: 5 year: 2011 end-page: 19 article-title: Fast simulation of skeleton‐driven deformable body characters publication-title: ACM Transactions on Graphics – volume: 29 start-page: 309 issue: 2 year: 2010 end-page: 318 article-title: Multi‐scale geometry interpolation publication-title: Computer Graphics Forum – volume: 35 start-page: 2201 issue: 3 year: 2008 end-page: 2214 article-title: Algorithm 887: CHOLMOD, supernodal sparse cholesky factorization and update/downdate publication-title: ACM Transactions on Mathematical Software – volume: 24 start-page: 479 issue: 3 year: 2005 end-page: 487 article-title: Linear rotation‐invariant coordinates for meshes publication-title: ACM Transactions on Graphics – volume: 26 start-page: 1 issue: 3 year: 2007 end-page: 8 article-title: Geometric modeling in shape space publication-title: ACM Transactions on Graphics – volume: 31 start-page: 1755 issue: 5 year: 2012 end-page: 1764 article-title: Time‐discrete geodesics in the space of shells publication-title: Computer Graphics Forum – volume: 30 start-page: 1 issue: 6 year: 2011 end-page: 12 article-title: Shape space exploration of constrained meshes publication-title: ACM Transactions on Graphics – volume: 28 start-page: 1 issue: 3 year: 2009 end-page: 6 article-title: Semantic deformation transfer publication-title: ACM Transactions on Graphics (TOG) – volume: 24 start-page: 399 issue: 3 year: 2005 end-page: 407 article-title: Skinning mesh animations publication-title: ACM Transactions on Graphics – volume: 27 start-page: 1 issue: 3 year: 2008 end-page: 8 article-title: Example‐based dynamic skinning in real time publication-title: ACM Transactions on Graphics – volume: 27 start-page: 1539 issue: 6 year: 2008 end-page: 1556 article-title: A survey on mesh segmentation techniques publication-title: Computer Graphics Forum – start-page: 301 year: 2005 end-page: 310 – volume: 23 start-page: 399 issue: 3 year: 2004 end-page: 405 article-title: Deformation transfer for triangle meshes publication-title: ACM Transactions on Graphics – volume: 26 start-page: 147 issue: 2 year: 2010 end-page: 155 article-title: Segmenting animated objects into near‐rigid components publication-title: The Visual Computer – start-page: 2199 year: 2000 end-page: 2202 – volume: 33 start-page: 1065 issue: 5 year: 2011 end-page: 1071 article-title: Shape recognition with spectral distances publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – year: 2010 – volume: 31 start-page: 735 issue: 2 year: 2012 end-page: 744 article-title: A continuous, editable representation for deforming mesh sequences with separate signals for time, pose and shape publication-title: Computer Graphics Forum – start-page: 62 volume-title: Proceedings of the 2003 ACM SIGGRAPH/Eurographics Symposium on Computer Animation year: 2003 ident: e_1_2_6_10_1 – ident: e_1_2_6_25_1 doi: 10.1145/2070781.2024158 – ident: e_1_2_6_19_1 doi: 10.1111/j.1467-8659.2007.01103.x – ident: e_1_2_6_2_1 – ident: e_1_2_6_23_1 doi: 10.1007/s00371-009-0394-5 – ident: e_1_2_6_16_1 doi: 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| Snippet | Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common... |
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| StartPage | 258 |
| SubjectTerms | Analysis Articulated Compatibility computational geometry Computer graphics digital geometry processing I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Hierarchy and geometric transformations Interpolation shape blending/morphing State of the art Studies Triangles |
| Title | Efficient Interpolation of Articulated Shapes Using Mixed Shape Spaces |
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| Volume | 32 |
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