Learning pullback HMM distances

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 36, Issue 7, 2014, Pages 1483-1489

  Cuzzolin, Fabio ^a   Sapienza, Michael ^a  

^a OXFORD BROOKES UNIVERSITY   (United Kingdom)

Author keywords

action recognition; Distance learning; hidden Markov models; pullback metrics

Indexed keywords

DISTANCE EDUCATION;

ACTION RECOGNITION; AUTOMORPHISMS; DISTANCE FUNCTIONS; DYNAMICAL MODEL; LOCAL FEATURE; MODEL SPACES; PULLBACK METRICS; TRAINING SETS;

HIDDEN MARKOV MODELS;

EID: 84903185642     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.181     Document Type: Article

References (33)

1. S. Ali, A. Basharat, and M. Shah, "Chaotic Invariants for Human Action Recognition," Proc. IEEE 11th Int'l Conf. Computer Vision (ICCV'07), 2007
2. M. Blank et al., "Actions as Space-Time Shapes," Proc. IEEE 10th Int'l Conf. Computer Vision (ICCV'05), pp. 1395-1402, 2005 (Pubitemid 44042342)
3. M.E.H. Benbouzid, "Bibliography on Induction Motors Faults Detection and Diagnosis," IEEE Trans. Energy Conversion, vol. 14, no. 4, pp. 1065-1074, Dec. 1999
4. P. Burman, "A Comparative Study of Ordinary Cross-Validation, V-Fold Cross-Validation and the Repeated Learning-Testing Methods," Biometrika, vol. 76, no. 3, pp. 503-514, 1989
5. R. Chaudhry et al., "Histograms of Oriented Optical Flow and Binet-Cauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'09), pp. 1932-1939, 2009
6. F. Cuzzolin, "Manifold Learning for Multi-Dimensional Auto-Regressive Dynamical Models," Machine Learning for Vision-Based Motion Analysis. Springer, 2011
7. M. Do, "Fast Approximation of Kullback-Leibler Distance for Dependence Trees and Hidden Markov Models," IEEE Signal Processing Letters, vol. 10, no. 4, pp. 115-118, Apr. 2003
8. R. Elliot, L. Aggoun, and J. Moore, Hidden Markov Models: Estimation and Control. Springer, 1995
9. S. Fine, Y. Singer, and N. Tishby, "The Hierarchical Hidden Markov Model: Analysis and Applications," Machine Learning, vol. 32, no. 1, pp. 41-62, 1998
10. A. Galata, N. Johnson, and D. Hogg, "Learning Variable-Length Markov Models of Behavior," Computer Vision and Image Understanding (CVIU), vol. 81, no. 3, pp. 398-413, 2001 (Pubitemid 32415983)
11. A. Gupta, P. Srinivasan, J. Shi, and L.S. Davis, "Understanding Videos, Constructing Plots Learning a Visually Grounded Storyline Model from Annotated Videos," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'09), pp. 2012-2019, 2009
12. B. Hanzon and R. Peeters, "Aspects of Fisher Geometry for Stochastic Linear Systems," Open Problems in Math. Systems and Control Theory, pp. 27-30, Springer, 2002
13. T.S. Jaakkola and D. Haussler, "Exploiting Generative Models in Discriminative Classifiers," Proc. Conf. Advances in Neural Information Processing Systems II (NIPS'99), pp. 487-493, 1999
14. E. Keogh, K. Chakrabarti, M. Pazzani, and S. Mehrotra, "Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases," J. Knowledge and Information Systems, vol. 3, pp. 263-286, 2000
15. T. Kim and R. Cipolla, "Canonical Correlation Analysis of Video Volume Tensors for Action Categorization and Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 8, pp. 1415-1428, 2009
16. H. Kuehne, H. Jhuang, E. Garrote, T. Poggio, and T. Serre, "HMDB: A Large Video Database for Human Motion Recognition," Proc. IEEE Int'l Conf. Computer Vision (ICCV'11), pp. 2556-2563, 2011
17. J.D. Lafferty and G. Lebanon, "Diffusion Kernels on Statistical Manifolds," J. Machine Learning Research, vol. 6, pp. 129-163, 2005
18. I. Laptev and T. Lindeberg, "Local Descriptors for Spatiotemporal Recognition," Proc. IEEE Int'l Conf. Computer Vision (ICCV'03), 2003
19. I. Laptev et al., "Learning Realistic Human Actions from Movies," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'08), 2008
20. G. Lebanon, "Flexible Metric Nearest Neighbor Classification," Proc. Uncertainty in Artificial Intelligence Conf. (UAI), 2003
21. G. Lebanon, "Metric Learning for Text Documents," IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), vol. 28, no. 4, pp. 497-508, Apr. 2006 (Pubitemid 43264649)
22. R. Li and R. Chellappa, "Aligning Spatio-Temporal Signals on a Special Manifold," Proc. 11th European Conf. Computer Vision (ECCV'10), 2010
23. J. Liu, J. Luo, and M. Shah, "Recognising Realistic Actions from Videos "in the Wild"," Proc. IEEE Conf. Computer Vision and Pattern Recognition (BMVC'09), 2009
24. E. Manios et al., "Life Threatening Ventricular Arrhythmias in Patients with Minimal or No Structural Heart Disease: Xperience with the Implantable Cardioverter Defibrillator," http://www.heartweb.org/heartweb/ 0197/icd0003.htm, 2014
25. M. Marszaek, I. Laptev, and C. Schmid, "Actions in Context," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'09), pp. 2929-2936, 2009
26. P. Petersen, Riemannian Geometry. Springer-Verlag, 1992
27. S. Roweis and L. Saul, "Nonlinear Dimensionality Reduction by Locally Linear Embedding," Science, vol. 290, no. 5500, pp. 2323-2326, 2000 (Pubitemid 32041578)
28. N. Shental, T. Hertz, D. Weinshall, and M. Pavel, "Adjustment Learning and Relevant Component Analysis," Proc. Seventh European Conf. Computer Vision-Part IV (ECCV'02), pp. 776-792, 2002
29. B. Scholkopf, "Statistical Learning and Kernel Methods," 2000
30. Q. Shi, L. Wang, L. Cheng, and A. Smola, "Discriminative Human Action Segmentation and Recognition Using Semi-Markov Model," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'08), pp. 1-8, 2008
31. P. Sykacek and S. Roberts, "Bayesian Time Series Classification," Advances in Neural Processing Systems, vol. 14, pp. 937-944, 2002
32. P.K. Turaga, A. Veeraraghavan, and R. Chellappa, "Statistical Analysis on Stiefel and Grassmann Manifolds with Applications in Computer Vision," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'08), pp. 1-8, 2008
33. H. Wang, A. Kl€aser, C. Schmid, and C. Liu, "Action Recognition by Dense Trajectories," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'11), 2011.