research-article

Space-time surface reconstruction using incompressible flow

Authors:

Dan A. Alcantara,

Thomas Lewiner,

Daniel Cohen-OrAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 27, Issue 5

Article No.: 110, Pages 1 - 10

https://doi.org/10.1145/1409060.1409063

Published: 01 December 2008 Publication History

Abstract

We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time solid, made up of spatial slices, each of which is a three-dimensional solid bounded by a watertight manifold. The motion of the object is described as an incompressible flow of material through time. We optimize the flow so that the distance material moves from one time frame to the next is bounded, the density of material remains constant, and the object remains compact. This formulation overcomes deficiencies in the acquired data, such as persistent occlusions, errors, and missing frames. We demonstrate the performance of our flow-based technique by reconstructing coherent sequences of watertight models from incomplete scanner data.

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References

[1]

de Aguiar, E., Zayer, R., Theobalt, C., Magnor, M., and Seidel, H.-P. 2007. Video-driven animation of human body scans. In 3DTV, IEEE, 1--4.

[2]

Allen, B., Curless, B., and Popovic, Z. 2002. Articulated body deformation from range scan data. In Siggraph, ACM, 612--619.

[3]

Anguelov, D., Koller, D., Pang, H.-C., Srinivasan, P., and Thrun, S. 2004. Recovering Articulated Object Models from 3D Range Data. In Uncertainty in Artificial Intelligence, Morgan Kaufmann, 18--26.

[4]

Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., and Davis, J. 2005. SCAPE: shape completion and animation of people. Transactions on Graphics 24, 3, 408--416.

Digital Library

[5]

Anuar, N., and Guskov, I. 2004. Extracting Animated Meshes with Adaptive Motion Estimation. In Vision, Modeling, and Visualization, IOS, 63--71.

[6]

Barron, J. L., and Thacker, N. A. 2004. Tutorial: Computing 2D and 3D Optical Flow. Tech. Rep. 012, Tina Memo.

[7]

Bradley, D., Popa, T., Sheffer, A., Heidrich, W., and Boubekeur, T. 2008. Markerless Garment Capture. In Siggraph, ACM.

[8]

Carranza, J., Theobalt, C., Magnor, M., and Seidel, H.-P. 2003. Free-viewpoint video of human actors. In Siggraph, ACM, 569--577.

[9]

Fong, P., and Buron, F. 2005. Sensing Deforming and Moving Objects with Commercial Off the Shelf Hardware. In Computer Vision and Pattern Recognition, IEEE, 101.

[10]

Goldlücke, B., and Magnor, M. 2005. Spacetime-continuous geometry meshes from multi-view video sequences. In International Conference on Image Processing, IEEE, 625--628.

[11]

Goldlücke, B., Ihrke, I., Linz, C., and Magnor, M. 2007. Weighted Minimal Hypersurface Reconstruction. Transactions on Pattern Analysis and Machine Intelligence 29, 7, 1194--1208.

Digital Library

[12]

Golub, G. H., and Greif, C. 2003. On solving block structured indefinite linear systems. Journal on Scientific Computing 24, 6, 2076--2092. SIAM.

Digital Library

[13]

Greif, C., and Schötzau, D. 2006. Preconditioners for Saddle Point Linear Systems with Highly Singular (1,1) Blocks. Electronic Transactions on Numerical Analysis 22, 114--121.

[14]

Grosso, E., Sandini, G., and Tistarelli, M. 1989. 3D object reconstruction using stereo and motion. Systems, Man and Cybernetics 19, 6, 1465--1476.

[15]

Gupta, N. C., and Kanal, L. N. 1995. 3D Motion Estimation from Motion Field. Artificial Intelligence 78, 1--2, 45--86.

Digital Library

[16]

Guskov, I., Klibanov, S., and Bryant, B. 2003. Trackable surfaces. In Symposium on Computer Animation, ACM/Eurographics, 251--257.

Digital Library

[17]

Hansen, P. C. 1998. Rank-Deficient and Discrete Ill-Posed Problems. SIAM.

[18]

Holland, P., and Welsch, R. 1977. Robust regression using iteratively reweighted least-squares. Communications in Statistics - Theory and Methods 6, 9, 813 -- 827.

[19]

Koninckx, T. P., and van Gool, L. J. 2006. Real-Time Range Acquisition by Adaptive Structured Light. Transactions on Pattern Analysis and Machine Intelligence 28, 3, 432--445.

Digital Library

[20]

Levin, A., Fergus, R., Durand, F., and Freeman, W. 2007. Image and depth from a conventional camera with a coded aperture. In Siggraph, ACM, 70.

[21]

Magnor, M., and Goldlücke, B. 2004. Spacetime-Coherent Geometry Reconstruction from Multiple Video Streams. In 3D Data Processing, Visualization and Transmission, IEEE, 365--372.

[22]

Marschner, S. R., Guenter, B. K., and Raghupathy, S. 2000. Modeling and Rendering for Realistic Facial Animation. In Rendering Techniques, Eurographics, 231--242.

[23]

Mitra, N. J., Flüry, S., Ovsjanikov, M., Gelfand, N., Guibas, L. J., and Pottmann, H. 2007. Dynamic geometry registration. In Symposium on Geometry Processing, ACM/Eurographics, 173--182.

Digital Library

[24]

Ohtake, Y., Belyaev, A., Alexa, M., Turk, G., and Seidel, H.-P. 2003. Multi-level partition of unity implicits. In Siggraph, ACM, 463--470.

[25]

Pekelny, Y., and Gotsman, C. 2008. Articulated object reconstruction and motion capture from depth video. In Eurographics, Eurographics, to appear.

[26]

Rusinkiewicz, S., Hall-Holt, O. A., and Levoy, M. 2002. Real-time 3D model acquisition. In Siggraph, ACM, 438--446.

[27]

Sharf, A., Lewiner, T., Shklarski, G., Toledo, S., and Cohen-Or, D. 2007. Interactive topology-aware surface reconstruction. In Siggraph, ACM, 43.

[28]

Shinya, M. 2004. Unifying Measured Point Sequences of Deforming Objects. In 3D Data Processing, Visualization and Transmission, IEEE, 904--911.

[29]

Toledo, S., 2003. TAUCS: A library of sparse linear solvers. version 2.2.

[30]

Ullman, S. 1979. The interpretation of structure from motion. Biological Sciences B 203, 1153, 405--426.

[31]

Vedula, S., Baker, S., Rander, P., Collins, R. T., and Kanade, T. 1999. Three-Dimensional Scene Flow. In International Conference on Computer Vision, IEEE, 722--729.

Digital Library

[32]

Wand, M., Jenke, P., Huang, Q., Bokeloh, M., Guibas, L. J., and Schilling, A. 2007. Reconstruction of deforming geometry from time-varying point clouds. In Symposium on Geometry Processing, ACM/Eurographics, 49--58.

Digital Library

[33]

Wang, Y., Gupta, M., 0002, S. Z., Wang, S., Gu, X., Samaras, D., and Huang, P. 2005. High Resolution Tracking of Non-Rigid 3D Motion of Densely Sampled Data Using Harmonic Maps. In International Conference on Computer Vision, IEEE, 388--395.

[34]

White, R., Crane, K., and Forsyth, D. A. 2007. Capturing and animating occluded cloth. In Siggraph, ACM, 34.

[35]

Zhang, L., Brian Curless, B., and Seitz, S. M. 2003. Spacetime faces: high resolution capture for modeling and animation. In Computer Vision and Pattern Recognition, IEEE, 367--374.

[36]

Zhang, L., Snavely, N., Curless, B., and Seitz, S. M. 2004. Spacetime faces: high resolution capture for modeling and animation. Transactions on Graphics 23, 3, 548--558.

Digital Library

Cited By

Castelo ANakassima GBueno LGameiro M(2024)A generalized combinatorial marching hypercube algorithmComputational and Applied Mathematics10.1007/s40314-024-02627-443:3Online publication date: 26-Mar-2024
https://doi.org/10.1007/s40314-024-02627-4
Moschella LMelzi SCosmo LMaggioli FLitany OOvsjanikov MGuibas LRodolà E(2022)Learning Spectral Unions of Partial Deformable 3D ShapesComputer Graphics Forum10.1111/cgf.1448341:2(407-417)Online publication date: 24-May-2022
https://doi.org/10.1111/cgf.14483
Dvořák JKáčereková ZVaněček PHruda LVáša L(2022)As-rigid-as-possible volume tracking for time-varying surfacesComputers and Graphics10.1016/j.cag.2021.10.015102:C(329-338)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.cag.2021.10.015
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Index Terms

Space-time surface reconstruction using incompressible flow
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 27, Issue 5

December 2008

552 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1409060

Issue’s Table of Contents

Copyright © 2008 ACM.

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Publication History

Published: 01 December 2008

Published in TOG Volume 27, Issue 5

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Cited By

Castelo ANakassima GBueno LGameiro M(2024)A generalized combinatorial marching hypercube algorithmComputational and Applied Mathematics10.1007/s40314-024-02627-443:3Online publication date: 26-Mar-2024
https://doi.org/10.1007/s40314-024-02627-4
Moschella LMelzi SCosmo LMaggioli FLitany OOvsjanikov MGuibas LRodolà E(2022)Learning Spectral Unions of Partial Deformable 3D ShapesComputer Graphics Forum10.1111/cgf.1448341:2(407-417)Online publication date: 24-May-2022
https://doi.org/10.1111/cgf.14483
Dvořák JKáčereková ZVaněček PHruda LVáša L(2022)As-rigid-as-possible volume tracking for time-varying surfacesComputers and Graphics10.1016/j.cag.2021.10.015102:C(329-338)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.cag.2021.10.015
Castelo ABueno LGameiro M(2021)A combinatorial marching hypercubes algorithmComputers & Graphics10.1016/j.cag.2021.10.023Online publication date: Nov-2021
https://doi.org/10.1016/j.cag.2021.10.023
Yu TZhao JZheng ZGuo KDai QLi HPons-Moll GLiu Y(2020)DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth SensorIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2019.292829642:10(2523-2539)Online publication date: 1-Oct-2020
https://doi.org/10.1109/TPAMI.2019.2928296
Ciucanu ABhandari NWu XRavikumar SYang YCosker DCharalambous PChrysanthou YJones BLee J(2018)E-StopMotionProceedings of the 11th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3274247.3274505(1-11)Online publication date: 8-Nov-2018
https://dl.acm.org/doi/10.1145/3274247.3274505
Savoye Y(2018)Cage-based performance captureACM SIGGRAPH 2018 Courses10.1145/3214834.3214836(1-72)Online publication date: 12-Aug-2018
https://dl.acm.org/doi/10.1145/3214834.3214836
Afzal HAouada DMirbach BOttersten B(2018)Full 3D Reconstruction of Non-Rigidly Deforming ObjectsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/317775614:1s(1-23)Online publication date: 26-Mar-2018
https://dl.acm.org/doi/10.1145/3177756
Zollhöfer MStotko PGörlitz ATheobalt CNießner MKlein RKolb A(2018)State of the Art on 3D Reconstruction with RGB‐D CamerasComputer Graphics Forum10.1111/cgf.1338637:2(625-652)Online publication date: 22-May-2018
https://doi.org/10.1111/cgf.13386
Yu TZheng ZGuo KZhao JDai QLi HPons-Moll GLiu Y(2018)DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2018.00761(7287-7296)Online publication date: Jun-2018
https://doi.org/10.1109/CVPR.2018.00761
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