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2016 | OriginalPaper | Buchkapitel

Capturing Dynamic Textured Surfaces of Moving Targets

verfasst von : Ruizhe Wang, Lingyu Wei, Etienne Vouga, Qixing Huang, Duygu Ceylan, Gérard Medioni, Hao Li

Erschienen in: Computer Vision – ECCV 2016

Verlag: Springer International Publishing

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Abstract

We present an end-to-end system for reconstructing complete watertight and textured models of moving subjects such as clothed humans and animals, using only three or four handheld sensors. The heart of our framework is a new pairwise registration algorithm that minimizes, using a particle swarm strategy, an alignment error metric based on mutual visibility and occlusion. We show that this algorithm reliably registers partial scans with as little as 15 % overlap without requiring any initial correspondences, and outperforms alternative global registration algorithms. This registration algorithm allows us to reconstruct moving subjects from free-viewpoint video produced by consumer-grade sensors, without extensive sensor calibration, constrained capture volume, expensive arrays of cameras, or templates of the subject geometry.

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Literatur
1.
de Aguiar, E., Stoll, C., Theobalt, C., Ahmed, N., Seidel, H.P., Thrun, S.: Performance capture from sparse multi-view video. In: ACM SIGGRAPH, pp. 98:1–98:10. ACM, New York (2008)
2.
Ahmed, N., Theobalt, C., Dobrev, P., Seidel, H.P., Thrun, S.: Robust fusion of dynamic shape and normal capture for high-quality reconstruction of time-varying geometry. In: IEEE CVPR, pp. 1–8, June 2008
3.
Aiger, D., Mitra, N.J., Cohen-Or, D.: 4-points congruent sets for robust pairwise surface registration. In: ACM Transactions on Graphics (TOG), vol. 27, p. 85. ACM (2008)
4.
Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., Davis, J.: Scape: shape completion and animation of people. ACM Trans. Graph. 24(3), 408–416 (2005)CrossRef
5.
Bogo, F., Black, M.J., Loper, M., Romero, J.: Detailed full-body reconstructions of moving people from monocular RGB-D sequences, pp. 2300–2308, December 2015
6.
Bojsen-Hansen, M., Li, H., Wojtan, C.: Tracking surfaces with evolving topology. ACM Trans. Graph. (SIGGRAPH 2012) 31(4), 53:1–53:10 (2012)
7.
Chen, C.S., Hung, Y.P., Cheng, J.B.: Ransac-based darces: a new approach to fast automatic registration of partially overlapping range images. IEEE Trans. Pattern Anal. Mach. Intell. 21(11), 1229–1234 (1999)CrossRef
8.
Chen, Y., Medioni, G.: Object modeling by registration of multiple range images. In: ICRA, pp. 2724–2729. IEEE (1991)
9.
Chuang, M., Luo, L., Brown, B.J., Rusinkiewicz, S., Kazhdan, M.: Estimating the laplace-beltrami operator by restricting 3D functions. In: Computer Graphics Forum, vol. 28, pp. 1475–1484. Wiley Online Library (2009)
10.
Chung, D.H., Yun, I.D., Lee, S.U.: Registration of multiple-range views using the reverse-calibration technique. Pattern Recogn. 31(4), 457–464 (1998)CrossRef
11.
Collet, A., Chuang, M., Sweeney, P., Gillett, D., Evseev, D., Calabrese, D., Hoppe, H., Kirk, A., Sullivan, S.: High-quality streamable free-viewpoint video. In: ACM SIGGRAPH, vol. 34, pp. 69:1–69:13. ACM, July 2015
12.
Debevec, P.: The light stages and their applications to photoreal digital actors. In: SIGGRAPH Asia, Singapore, November 2012
13.
Dou, M., Taylor, J., Fuchs, H., Fitzgibbon, A., Izadi, S.: 3D scanning deformable objects with a single rgbd sensor. In: IEEE CVPR, pp. 493–501, June 2015
14.
Franco, J., Lapierre, M., Boyer, E.: Visual shapes of silhouette sets. In: Third International Symposium on 3D Data Processing, Visualization, and Transmission, pp. 397–404, June 2006
15.
Gelfand, N., Mitra, N.J., Guibas, L.J., Pottmann, H.: Robust global registration. In: Symposium on Geometry Processing, vol. 2, p. 5 (2005)
16.
Hernández, C., Schmitt, F., Cipolla, R.: Silhouette coherence for camera calibration under circular motion. IEEE Trans. Pattern Anal. Mach. Intell. 29(2), 343–349 (2007)CrossRef
17.
Horn, B.K.: Extended gaussian images. Proc. IEEE 72(12), 1671–1686 (1984)CrossRef
18.
Izadi, S., Kim, D., Hilliges, O., Molyneaux, D., Newcombe, R., Kohli, P., Shotton, J., Hodges, S., Freeman, D., Davison, A., Fitzgibbon, A.: Kinectfusion: real-time 3D reconstruction and interaction using a moving depth camera. In: UIST, pp. 559–568. ACM, New York (2011)
19.
Johnson, A.E., Hebert, M.: Using spin images for efficient object recognition in cluttered 3D scenes. IEEE Trans. Pattern Anal. Mach. Intell. 21(5), 433–449 (1999)CrossRef
20.
Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, vol. 7 (2006)
21.
Kennedy, J.: Particle swarm optimization. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning, pp. 760–766. Springer, New York (2010)
22.
Li, H., Adams, B., Guibas, L.J., Pauly, M.: Robust single-view geometry and motion reconstruction. In: ACM SIGGRAPH Asia, SIGGRAPH Asia 2009, pp. 175:1–175:10. ACM, New York (2009)
23.
Li, H., Luo, L., Vlasic, D., Peers, P., Popović, J., Pauly, M., Rusinkiewicz, S.: Temporally coherent completion of dynamic shapes. ACM TOG 31(1), 2:1–2:11 (2012)CrossRef
24.
Li, H., Vouga, E., Gudym, A., Luo, L., Barron, J.T., Gusev, G.: 3D self-portraits. In: ACM SIGGRAPH Asia, vol. 32, pp. 187:1–187:9. ACM, November 2013
25.
Li, H., Yu, J., Ye, Y., Bregler, C.: Realtime facial animation with on-the-fly correctives. In: ACM SIGGRAPH, vol. 32, pp. 42:1–42:10. ACM, July 2013
26.
Liu, Y., Ye, G., Wang, Y., Dai, Q., Theobalt, C.: Human performance capture using multiple handheld kinects. In: Shao, L., Han, J., Kohli, P., Zhang, Z. (eds.) Computer Vision and Machine Learning with RGB-D Sensors, pp. 91–108. Springer International Publishing, Cham (2014)
27.
Makadia, A., Patterson, A., Daniilidis, K.: Fully automatic registration of 3D point clouds. In: 2006 IEEE Conference on CVPR, vol. 1, pp. 1297–1304. IEEE (2006)
28.
Matusik, W., Buehler, C., Raskar, R., Gortler, S.J., McMillan, L.: Image-based visual hulls. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2000, pp. 369–374. ACM Press/Addison-Wesley Publishing Co., New York (2000)
29.
Mellado, N., Aiger, D., Mitra, N.J.: Super 4pcs fast global pointcloud registration via smart indexing. In: Computer Graphics Forum, vol. 33, pp. 205–215. Wiley Online Library (2014)
30.
Moezzi, S., Tai, L.C., Gerard, P.: Virtual view generation for 3D digital video. MultiMedia, IEEE 4(1), 18–26 (1997)CrossRef
31.
Newcombe, R.A., Fox, D., Seitz, S.M.: Dynamicfusion: reconstruction and tracking of non-rigid scenes in real-time. In: IEEE CVPR, June 2015
32.
Oikonomidis, I., Kyriazis, N., Argyros, A.A.: Tracking the articulated motion of two strongly interacting hands. In: IEEE CVPR, pp. 1862–1869. IEEE (2012)
33.
Qian, C., Sun, X., Wei, Y., Tang, X., Sun, J.: Realtime and robust hand tracking from depth. In: IEEE CVPR, pp. 1106–1113. IEEE (2014)
34.
Rusinkiewicz, S., Levoy, M.: Efficient variants of the icp algorithm. In: 3-D Digital Imaging and Modeling, pp. 145–152. IEEE (2001)
35.
Rusu, R.B., Blodow, N., Beetz, M.: Fast point feature histograms (fpfh) for 3D registration. In: 2009 IEEE International Conference on Robotics and Automation, pp. 3212–3217. IEEE (2009)
36.
Rusu, R.B., Blodow, N., Marton, Z.C., Beetz, M.: Aligning point cloud views using persistent feature histograms. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3384–3391. IEEE (2008)
37.
Rusu, R.B., Cousins, S.: 3D is here: point cloud library (pcl). In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 1–4. IEEE (2011)
38.
Shilane, P., Min, P., Kazhdan, M., Funkhouser, T.: The princeton shape benchmark. In: Shape modeling applications, 2004. Proceedings, pp. 167–178. IEEE (2004)
39.
Shoemake, K.: Uniform random rotations. In: Graphics Gems III, pp. 124–132. Academic Press Professional, Inc. (1992)
40.
Silva, L., Bellon, O.R., Boyer, K.L.: Precision range image registration using a robust surface interpenetration measure and enhanced genetic algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 27(5), 762–776 (2005)CrossRefMATH
41.
Starck, J., Hilton, A.: Surface capture for performance-based animation. IEEE Comput. Graph. Appl. 27(3), 21–31 (2007)CrossRef
42.
Süßmuth, J., Winter, M., Greiner, G.: Reconstructing animated meshes from time-varying point clouds. In: SGP, SGP 2008, pp. 1469–1476 (2008)
43.
Tevs, A., Berner, A., Wand, M., Ihrke, I., Bokeloh, M., Kerber, J., Seidel, H.P.: Animation cartography—intrinsic reconstruction of shape and motion. ACM TOG 31(2), 12:1–12:15 (2012)CrossRef
44.
Tong, J., Zhou, J., Liu, L., Pan, Z., Yan, H.: Scanning 3D full human bodies using kinects. IEEE TVCG 18(4), 643–650 (2012)
45.
Vlasic, D., Baran, I., Matusik, W., Popović, J.: Articulated mesh animation from multi-view silhouettes. In: ACM SIGGRAPH, SIGGRAPH 2008, pp. 97:1–97:9. ACM, New York (2008)
46.
Vlasic, D., Peers, P., Baran, I., Debevec, P., Popović, J., Rusinkiewicz, S., Matusik, W.: Dynamic shape capture using multi-view photometric stereo. In: ACM SIGGRAPH Asia, SIGGRAPH Asia 2009. pp. 174:1–174:11 (2009)
47.
Wand, M., Adams, B., Ovsjanikov, M., Berner, A., Bokeloh, M., Jenke, P., Guibas, L., Seidel, H.P., Schilling, A.: Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data. ACM TOG 28(2), 15:1–15:15 (2009)CrossRef
48.
Wand, M., Jenke, P., Huang, Q., Bokeloh, M., Guibas, L., Schilling, A.: Reconstruction of deforming geometry from time-varying point clouds. In: SGP, SGP 2007, pp. 49–58 (2007)
49.
Wang, R., Choi, J., Medioni, G.: 3D modeling from wide baseline range scans using contour coherence. In: 2014 IEEE Conference on CVPR, pp. 4018–4025 (2014)
50.
Wei, L., Huang, Q., Ceylan, D., Vouga, E., Li, H.: Dense human body correspondences using convolutional networks. In: IEEE CVPR. IEEE (2016)
51.
Wu, C., Stoll, C., Valgaerts, L., Theobalt, C.: On-set performance capture of multiple actors with a stereo camera. ACM Trans. Graph. 32(6), 161:1–161:11 (2013)
52.
Wu, C., Varanasi, K., Liu, Y., Seidel, H.P., Theobalt, C.: Shading-based dynamic shape refinement from multi-view video under general illumination, pp. 1108–1115. IEEE, November 2011
53.
Yang, J., Li, H., Jia, Y.: Go-icp: Solving 3D registration efficiently and globally optimally. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 1457–1464. IEEE (2013)
54.
Ye, G., Deng, Y., Hasler, N., Ji, X., Dai, Q., Theobalt, C.: Free-viewpoint video of human actors using multiple handheld kinects. IEEE Trans. Cybern. 43(5), 1370–1382 (2013)CrossRef
55.
Zhang, Z.: Iterative point matching for registration of free-form curves and surfaces. IJCV 13(2), 119–152 (1994)CrossRef
56.
Zollhöfer, M., Nießner, M., Izadi, S., Rehmann, C., Zach, C., Fisher, M., Wu, C., Fitzgibbon, A., Loop, C., Theobalt, C., Stamminger, M.: Real-time non-rigid reconstruction using an rgb-d camera. In: ACM SIGGRAPH, vol. 33, pp. 156:1–156:12. ACM, New York, July 2014
Metadaten
Titel
Capturing Dynamic Textured Surfaces of Moving Targets
verfasst von
Ruizhe Wang
Lingyu Wei
Etienne Vouga
Qixing Huang
Duygu Ceylan
Gérard Medioni
Hao Li
Copyright-Jahr
2016
Buch
Computer Vision – ECCV 2016

Print ISBN: 978-3-319-46477-0

Electronic ISBN: 978-3-319-46478-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-46478-7_17