Dense human body correspondences using convolutional networks

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2016-December, Issue , 2016, Pages 1544-1553

  Wei, Lingyu ^a   Huang, Qixing ^b   Ceylan, Duygu ^c   Vouga, Etienne ^d   Li, Hao ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO   (United States)

^c ADOBE RESEARCH   (United States)

^d UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; CONVOLUTION; HOSIERY MANUFACTURE; NEURAL NETWORKS;

CONVOLUTIONAL NETWORKS; CONVOLUTIONAL NEURAL NETWORK; DENSE CORRESPONDENCES; FEATURE DESCRIPTORS; GEOMETRIC INFORMATION; RECONSTRUCTED SURFACES; SHAPE CORRESPONDENCES; UNSUPERVISED METHOD;

PATTERN RECOGNITION;

EID: 84986309327     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.171     Document Type: Conference Paper

References (49)

1. 3d animation online services, 3d characters, and character rigging-mixamo. https: //www. mixamo. com/. Accessed: 2015-10-03.
2. Yobi3d-free 3d model search engine. https: //www. yobi3d. com. Accessed: 2015-11-03.
3. D. Anguelov, P. Srinivasan, H. cheung Pang, D. Koller, S. Thrun, and J. Davis. The correlated correspondence algorithm for unsupervised registration of nonrigid surfaces. In NIPS, pages 33-40. MIT Press, 2004.
4. D. Anguelov, P. Srinivasan, D. Koller, S. Thrun, J. Rodgers, and J. Davis. Scape: Shape completion and animation of people. In ACM TOG (Siggraph), pages 408-416, 2005.
5. M. Aubry, U. Schlickewei, and D. Cremers. The wave kernel signature: A quantum mechanical approach to shape analysis. In IEEE ICCV Workshops, 2011.
6. F. Bogo, M. J. Black, M. Loper, and J. Romero. Detailed full-body reconstructions of moving people from monocular RGB-D sequences. In IEEE ICCV, Dec. 2015.
7. F. Bogo, J. Romero, M. Loper, and M. J. Black. FAUST: Dataset and evaluation for 3D mesh registration. In IEEE CVPR, 2014.
8. A. Bronstein, M. Bronstein, R. Kimmel, M. Mahmoudi, and G. Sapiro. A gromov-hausdorff framework with diffusion geometry for topologically-robust non-rigid shape matching. Int. Journal on Computer Vision, 89 (2-3): 266-286, 2010.
9. A. M. Bronstein, M. M. Bronstein, and R. Kimmel. Generalized multidimensional scaling: A framework for isometryinvariant partial surface matching. Proc. of the National Academy of Science, pages 1168-1172, 2006.
10. Q. Chen and V. Koltun. Robust nonrigid registration by convex optimization. In IEEE ICCV, 2015.
11. M. Dou, J. Taylor, H. Fuchs, A. Fitzgibbon, and S. Izadi. 3d scanning deformable objects with a single rgbd sensor. In IEEE CVPR, 2015.
12. A. Elad and R. Kimmel. On bending invariant signatures for surfaces. IEEE PAMI, 25 (10): 1285-1295, 2003.
13. P. Fischer, A. Dosovitskiy, E. Ilg, P. Häusser, C. Hazirbas, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox. Flownet: Learning optical flow with convolutional networks. CoRR, abs/1504. 06852, 2015.
14. R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2014.
15. X. Han, T. Leung, Y. Jia, R. Sukthankar, and A. C. Berg. Matchnet: Unifying feature and metric learning for patchbased matching. 2015.
16. Q.-X. Huang, B. Adams, M. Wicke, and L. J. Guibas. Nonrigid registration under isometric deformations. In CGF (SGP), pages 1449-1457, 2008.
17. V. Jain and H. Zhang. Robust 3d shape correspondence in the spectral domain. In SMI, page 19. IEEE Computer Society, 2006.
18. A. E. Johnson and M. Hebert. Using spin images for efficient object recognition in cluttered 3d scenes. IEEE PAMI, 21 (5): 433-449, May 1999.
19. V. G. Kim, Y. Lipman, X. Chen, and T. Funkhouser. Möbius Transformations For Global Intrinsic Symmetry Analysis. In CGF (SGP), 2010.
20. V. G. Kim, Y. Lipman, and T. Funkhouser. Blended Intrinsic Maps. In ACM TOG (Siggraph), volume 30, 2011.
21. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, pages 1097-1105. 2012.
22. M. Leordeanu and M. Hebert. A spectral technique for correspondence problems using pairwise constraints. In IEEE ICCV, pages 1482-1489, Washington, DC, USA, 2005.
23. H. Li, B. Adams, L. J. Guibas, and M. Pauly. Robust singleview geometry and motion reconstruction. In ACM TOG (Siggraph Asia), 2009.
24. H. Li, E. Vouga, A. Gudym, L. Luo, J. T. Barron, and G. Gusev. 3d self-portraits. In ACM TOG (Siggraph Asia), 2013.
25. Y. Lipman and T. Funkhouser. Möbius voting for surface correspondence. In ACM TOG (Siggraph), pages 72: 1-72: 12, 2009.
26. R. Litman and A. Bronstein. Learning spectral descriptors for deformable shape correspondence. IEEE PAMI, 36 (1): 171-180, 2014.
27. J. L. Long, N. Zhang, and T. Darrell. Do convnets learn correspondence In NIPS, pages 1601-1609. 2014.
28. J. Masci, D. Boscaini, M. M. Bronstein, and P. Vandergheynst. Geodesic convolutional neural networks on riemannian manifolds. In The IEEE International Conference on Computer Vision (ICCV) Workshops, December 2015.
29. R. A. Newcombe, D. Fox, and S. M. Seitz. Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time. In IEEE CVPR, 2015.
30. M. Ovsjanikov, Q. Mérigot, F. Mémoli, and L. J. Guibas. One point isometric matching with the heat kernel. CGF, 29 (5): 1555-1564, 2010.
31. G. Pons-Moll, J. Taylor, J. Shotton, A. Hertzmann, and A. Fitzgibbon. Metric regression forests for correspondence estimation. International Journal of Computer Vision, 113 (3): 163-175, 2015.
32. H. Pottmann, J. Wallner, Q.-X. Huang, and Y.-L. Yang. Integral invariants for robust geometry processing. Computer Aided Geometric Design, 26 (1): 37-60, 2009.
33. E. Rodola, S. Rota Bulo, T. Windheuser, M. Vestner, and D. Cremers. Dense non-rigid shape correspondence using random forests. 2014.
34. S. Rusinkiewicz, B. Brown, and M. Kazhdan. 3d scan matching and registration. In ICCV 2005 Short Course, 2005.
35. R. M. Rustamov. Laplace-beltrami eigenfunctions for deformation invariant shape representation. In CGF (SGP), pages 225-233, 2007.
36. F. Schroff, D. Kalenichenko, and J. Philbin. Facenet: A unified embedding for face recognition and clustering. CoRR, abs/1503. 03832, 2015.
37. P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. CoRR, abs/1312. 6229, 2013.
38. J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore, P. Kohli, A. Criminisi, A. Kipman, and A. Blake. Efficient human pose estimation from single depth images. IEEE PAMI, 2012.
39. J. Sun, M. Ovsjanikov, and L. Guibas. A concise and provably informative multi-scale signature based on heat diffusion. In CGF (SGP), pages 1383-1392, 2009.
40. J. Süssmuth, M. Winter, and G. Greiner. Reconstructing animated meshes from time-varying point clouds. Number 5, pages 1469-1476, 2008.
41. J. Taylor, J. Shotton, T. Sharp, and A. Fitzgibbon. The Vitruvian manifold: Inferring dense correspondences for oneshot human pose estimation. In Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, pages 103-110. IEEE, 2012.
42. A. Tevs, A. Berner, M. Wand, I. Ihrke, M. Bokeloh, J. Kerber, and H.-P. Seidel. Animation cartography-intrinsic reconstruction of shape and motion. ACMTOG, 31 (2): 12: 1-12: 15, Apr. 2012.
43. J. Tompson, M. Stein, Y. LeCun, and K. Perlin. Real-time continuous pose recovery of human hands using convolutional networks. ACM Transactions on Graphics (TOG), 33 (5): 169, 2014.
44. D. Vlasic, I. Baran, W. Matusik, and J. Popovíc. Articulated mesh animation from multi-view silhouettes. 2008.
45. M. Wand, B. Adams, M. Ovsjanikov, A. Berner, M. Bokeloh, P. Jenke, L. Guibas, H.-P. Seidel, and A. Schilling. Efficient reconstruction of nonrigid shape and motion from real-time 3d scanner data. ACM TOG, 28 (2), 2009.
46. X. Wei, P. Zhang, and J. Chai. Accurate realtime full-body motion capture using a single depth camera. ACM TOG, 31 (6): 188: 1-188: 12, Nov. 2012.
47. T. Windheuser, U. Schlickewei, F. Schmidt, and D. Cremers. Geometrically consistent elastic matching of 3d shapes: A linear programming solution. In IEEE ICCV, pages 2134-2141, 2011.
48. T. Windheuser, M. Vestner, E. Rodola, R. Triebel, and D. Cremers. Optimal intrinsic descriptors for non-rigid shape analysis. In British Machine Vision Conf., 2014.
49. S. Zagoruyko and N. Komodakis. Learning to compare image patches via convolutional neural networks. In IEEE CVPR, pages 4353-4361, 2015.