Coherent Laplacian 3-D protrusion segmentation

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Cuzzolin, Fabio ^a   Mateusy, Diana ^a   Knossow, David ^a   Boyer, Edmond ^a   Horaud, Radu ^a  

^a INRIA RHÔNE ALPES   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; CLUSTER ANALYSIS; COMPUTER VISION; FEATURE EXTRACTION; FLOW OF SOLIDS; IMAGE PROCESSING; PATTERN RECOGNITION; TOPOLOGY;

AFFINE CO ORDINATES; CURVATURE REGIONS; EM CLUSTERING; GROUND TRUTH; LAPLACIAN; LOCALLY LINEAR EMBEDDING; REAL DATA; TIME SEQUENCES;

THREE DIMENSIONAL;

EID: 51949103209     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587452     Document Type: Conference Paper

References (24)

1. S. Agarwal, J. Lim, L. Zelnik-Manor, P. Perona, D. Kriegman, and S. Belongie. Beyond pairwise clustering. In CVPR'05, 2005.
2. M. Belkin and P. Niyogi. Laplacian eigenmaps and spectral techniques for embedding and clustering. In NIPS'01, 2001.
3. M. Brand. Shadow puppetry. In ICCV'99, 1999.
4. A. M. Bronstein, M. M. Bronstein, and R. Kimmel. Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching. Proceedings of the National Academy of Sciences, 103(5):1168-1172, 2006.
5. G.-J. Brostow, I. Essa, D. Steedly, and V. Kwatra. Novel Skeletal Representation For Articulated Creatures. In ECCV'04, 2004.
6. C.-W. Chu, O. C. Jenkins, and M. J. Mataric. Marker-less kinematic model and motion capture from volume sequences. In CVPR'03, 2003.
7. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. J. Royal Stat. Soc., 39:1-38, 1977.
8. D. L. Donoho and C. Grimes. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data. Proceedings of the National Academy of Sciences, 100(10):5591-5596, 2003.
9. A. Elgammal and C. Lee. Inferring 3D body Pose from Silhouettes using Activity Manifold Learning. In CVPR'04, 2004.
10. D. Gavrila and L. Davis. 3D model-based tracking of humans in action: a multi-view approach . In CVPR'96, 1996.
11. K. Grauman, G. Shakhnarovich, and T. Darrell. Inferring 3d structure with a statistical image-based shape model. In ICCV'03, 2003.
12. D. Hogg. Model Based vision: a program to see a walking person. In Image and Vision Computing, 1983.
13. V. Jain and H. Zhang. Robust 3d shape correspondence in the spectral domain. In SMI'06, 2006.
14. O. Jenkins and M. Mataric. A spatio-temporal extension to isomap nonlinear dimension reduction. In ICML'04, 2004.
15. B. Lévy. Laplace-Beltrami eigenfunctions: Towards and algorithm that understands geometry. In SMI'06, 2006.
16. R. Lin, C.-B. Liu, M.-H. Yang, N. Ahuja, and S. Levinson. Learning Nonlinear Manifolds from Time Series. In ECCV'06, 2006.
17. T. Moeslund, A. Hilton, and V. Krüger. A survey of advances in vision based human motion capture and analysis. Computer Vision and Image Understanding, 104(2-3), 2006.
18. A. Ng, M. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS'01, 2001.
19. G. Rosman, A. Bronstein, M. Bronstein, and R. Kimmel. Manifold analysis by topologically constrained isometric embedding. International Journal of Applied Mathematics and Computer Sciences, 1(3):117-123, 2004.
20. S. Roweis and L. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500):2323-2326, 2000.
21. J. Shi and J. Malik. Normalized cuts and image segmentation. PAMI, 22(8):888-905, 2000.
22. A. Sundaresan and R. Chellappa. Segmentation and Probalistic Registration of Articulated Body Models. In ICPR'06, 2006.
23. J. B. Tenenbaum, V. d. Silva, and J. C. Langford. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 290(5500):2319-2323, 2000.
24. K. Zhou, J. Huang, J. Snyder, X. Liu, H. Bao, B. Guo, and H.-Y. Shum. Large mesh deformation using the volumetric graph laplacian. ACM Trans. Graph., 24(3):496-503, 2005.