Human action recognition based on 3d human modeling and cyclic HMMs

ETRI Journal

Volumn 36, Issue 4, 2014, Pages 662-672

  Ke, Shian Ru ^a   Uyen Thuc, Hoang Le ^b   Hwang, Jenq Neng ^a   Yoo, Jang Hee ^c   Choi, Kyoung Ho ^d  

^a University of Washington   (United States)

^b THE UNIVERSITY OF DANANG   (Viet Nam)

^c Electronics and Telecommunications Research Institute (ETRI)   (South Korea)

^d Mokpo National University   (South Korea)

Author keywords

3D modeling; Geometrical relational features; Hidden Markov model; Human action recognition

Indexed keywords

GESTURE RECOGNITION; HIDDEN MARKOV MODELS; IMAGE RECOGNITION;

3-D MODELING; CONTINUOUS ACTIONS; DIMENSIONALITY REDUCTION; EFFECTIVE PERFORMANCE; HUMAN-ACTION RECOGNITION; K-MEANS CLUSTERING; MONOCULAR VIDEO SEQUENCES; RELATIONAL FEATURES;

MOTION ESTIMATION;

EID: 84905966520     PISSN: 12256463     EISSN: 22337326     Source Type: Journal    
DOI: 10.4218/etrij.14.0113.0647     Document Type: Article

References (51)

1. M. Blank et al., "Actions as Space-Time Shapes," IEEE Int. Conf. Comput. Vis., Beijing, China, vol. 2, 2005, pp. 1395-1402
2. Y. Ke, R. Sukthankar, and M. Hebert, "Spatio-Temporal Shape and Flow Correlation for Action Recognition," IEEE CVPR, 2007
3. W. Kim, C. Jung, and C. Kim, "Spatiotemporal Saliency Detection and its Applications in Static and Dynamic Scenes," IEEE Trans. Circuits Syst. Video Technol., vol. 21, no. 4, Apr. 2011, pp. 446-456
4. I. Laptev, "On Space-Time Interest Points," Int. J. Comput. Vis., vol. 64, no. 2-3, Sept. 2005, pp. 107-123
5. I. Laptev et al., "Learning Realistic Human Actions from Movies," Proc. IEEE CVPR, Anchorage, AK, USA, June 23-28, 2008, pp. 1-8
6. S. Kumari and S.K. Mitra, "Human Action Recognition Using DFT," Proc. NCVPRIPG, Dec. 15-17, 2011, pp. 239-242
7. D.G. Lowe, "Object Recognition from Local Scale-Invariant Features," IEEE Int. Conf. Comput. Vis., Kerkira, Greece, vol. 2, 1999, pp. 1150-1157
8. D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int. J. Comput. Vis., vol. 60, no. 2, 2004, pp. 91-110
9. N. Dalal and B. Triggs, "Histograms of Oriented Gradients for Human Detection," IEEE CVPR, San Diego, CA, USA, vol. 1, June 25, 2005, pp. 886-893
10. C. Lin, F. Hsu, and W. Lin, "Recognizing Human Actions Using NWFE-Based Histogram Vectors," EURASIP J. Advances Signal Proc., vol. 2010, no. 9, Feb. 2010
11. B.D. Lucas and T. Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision," Int. Joint Conf. Artif. Intell., Vancouver, Canada, 1981, pp. 674-679
12. J. Shi and C. Tomasi, "Good Features to Track," IEEE CVPR, Seattle, WA, USA, June 1994, pp. 593-600
13. P. Scovanner, S. Ali, and M. Shah, "A 3-Dimensional SIFT Descriptor and its Application to Action Recognition," Proc. Int. Conf. Multimedia, Augsburg, Germany, 2007, pp. 357-360
14. W. Lu and J.J. Little, "Simultaneous Tracking and Action Recognition Using the PCA-HOG Descriptor," Canadian Conf. Comput. Robot Vis., June 7-9, 2006, p. 6
15. H. Kataoka and Y. Aoki, "Symmetrical Judgment and Improvement of CoHOG Feature Descriptor for Pedestrian Detection," IAPR Conf. Mach. Vis. Appl., Nara, Japan, June 13- 15, 2011, pp. 536-539
16. X. Lu, Q. Liu, and S. Oe, "Recognizing Non-rigid Human Actions Using Joints Tracking in Space-Time," Int. Conf. ITCC, Las Vegas, NW, USA, vol. 1, Apr. 5-7, 2004, pp. 620-624
17. D. Weinland, E. Boyer, and R. Ronfard, "Action Recognition from Arbitrary Views Using 3D Exemplars," IEEE Int. Conf. Comput. Vis., Rio de Janeiro, Brazil, Oct. 14-21, 2007, pp.1-7
18. I.N. Junejo et al., "View-Independent Action Recognition from Temporal Self-similarities," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 1, Jan. 2011, pp. 172-185
19. G. Rogez, J.J. Guerrero, and C. Orrite, "View-Invariant Human Feature Extraction for Video-Surveillance Applications," IEEE Conf. AVSS, London, UK, Sept. 5-7, 2007, pp. 324-329
20. M. Lee and R. Nevatia, "Body Part Detection for Human Pose Estimation and Tracking," IEEE Workshop Motion Video Comput., Austin, TX, USA, Feb. 2007
21. M. Lee and R. Nevatia, "Human Pose Tracking in Monocular Sequence Using Multilevel Structured Models," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 1, Jan. 2009, pp. 27-38
22. W. Gilks, S. Richardson, and D. Spiegelhalter, Markov Chain Monte Carlo in Practice, London, UK: Chapman and Hall, 1996
23. S. Zhu, R. Zhang, and Z. Tu, "Integrating Bottom-up/Top-down for Object Recognition by Data Driven Markov Chain Monte Carlo," IEEE CVPR, Hilton Head Island, SC, USA, vol. 1, 2000, pp. 738-745
24. S. Ke et al., "Real-Time 3D Human Pose Estimation from Monocular View with Applications to Event Detection and Video Gaming," IEEE Int. Conf. AVSS, Boston, MA, USA, Aug. 29-Sept. 1, 2010, pp. 489-496
25. S. Ke et al., "View-Invariant 3D Human Body Pose Reconstruction Using a Monocular Video Camera," ACM/IEEE ICDSC, Ghent, Belgium, Aug. 22-25, 2011, pp. 1-6
26. L.W. Campbell et al., "Invariant Features for 3-D Gesture Recognition," Proc. Int. Conf. Autom. Face Gesture Recogn., Killington, VT, USA, Oct. 14-16, 1996, pp. 157-162
27. M. Muller, T. Roder, and M. Clausen, "Efficient Content-Based Retrieval of Motion Capture Data," ACM SIGGRAPH, Los Angeles, CA, USA, vol. 24, no. 3, July 2005, pp. 677-685
28. H. Thuc et al., "Human Action Recognition Based on 3D Body Modeling from Monocular Videos," Frontiers Comput. Vis. Workshop, Kawasaki, Japan, Feb. 2-4, 2012, pp. 6-13
29. H. Thuc, P. Tuan, and J. Hwang, "An Effective 3D Geometric Relational Feature Descriptor for Human Action Recognition," IEEE Int. Conf. Comput. Commun. Tech. RIVF, Ho Chi Minh City, Vietnam, Feb. 27-Mar. 1, 2012, pp. 1-6
30. L. Rabiner and B. Juang, Fundamentals of Speech Recognition, 1st ed., Upper Saddle River, NJ: Prentice Hall, 1993
31. S. Sempena, N.U. Maulidevi, and P.R. Aryan, "Human Action Recognition Using Dynamic Time Warping," Int. Conf. Electr. Eng. Informat., Bandung, Indonesia, July 17-19, 2011, pp. 1-5
32. V.N. Vapnik, Statistical Learning Theory, New York: Wiley, 1998
33. V.N. Vapnik, S.E. Golowich, and A.J. Smola, "Support Vector Method for Function Approximation, Regression Estimation and Signal Processing," In M. C. Mozer, M. I. Jordan, and T. Petsche editors, Advances in Neural Information Processing Systems 9, Cambridge, MA: MIT Press, 1997
34. C. Schuldt, I. Laptev, and B. Caputo, "Recognizing Human Actions: A Local SVM Approach," Proc. IEEE Int. Conf. Pattern Recogn., Cambridge, UK, vol. 3, Aug. 23-26, 2004, pp. 32-36
35. L. Rabiner and B. Juang, "An Introduction to Hidden Markov Models," IEEE ASSP Mag., vol. 3, no. 1, Jan. 1986, pp. 4-16
36. J. Yamato, J. Ohya, and K. Ishii, "Recognizing Human Action in Time-Sequential Images Using Hidden Markov Model," IEEE CVPR, Champaign, IL, USA, June 15-18, 1992, pp. 379-385
37. M. Umeda, "Recognition of Multi-font Printed Chinese Characters," Proc. IEEE CVPR, Las Vegas, NV, USA, 1982, pp. 793-796
38. H. Thuc et al, "Quasi-Periodic Action Recognition from Monocular Videos via 3D Human Models and Cyclic HMMs," Int. Conf. ATC, Hanoi, Vietnam, Oct. 10-12, 2012, pp. 110-113
39. J.A. Hartigan and M.A. Wong, "Algorithm AS 136: A K-Means Clustering Algorithm," Appl. Statistics, New York: Wiley, 1979, pp. 100-108
40. J. Bilmes and G. Zweig, "The Graphical Models Toolkit: An Open Source Software System for Speech and Time-Series Processing," IEEE ICASSP, Orlando, FL, USA, vol. 4, May 13- 17, 2002, pp. 3916-3919
41. T. Horprasert, D. Harwood, and L.S. Davis, "A Statistical Approach for Real-Time Robust Background Subtraction and Shadow Detection," IEEE ICCV, Frame-Rate Workshop, Greece, Sept. 1999, pp. 1-19
42. S.A. Al-Shehri, "A Simple and Novel Method for Skin Detection and Face Locating and Tracking," Proc. APCHI, Rotorua, New Zealand, 2004, pp. 1-8
43. J. Canny, "A Computational Approach to Edge Detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 8, no. 6, Nov. 1986, pp. 679-698
44. D. Comaniciu and P. Meer, "Mean Shift: A Robust Approach toward Feature Space Analysis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, May 2002, pp. 603-619
45. D. Comaniciu, V. Ramesh, and P. Meer, "Kernel-Based Object Tracking," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 5, May 2003, pp. 564-577
46. G. Welch and G. Bishop, "An Introduction to the Kalman Filter," Technical Report TR 95-041, Department of Computer Science, University of North Carolina at Chapel Hill, 1995
47. W. Press et al., "Numerical Recipes in C++: The Art of Scientific Computing," Pearson Education, 1992
48. R.A. Wagner and M.J. Fischer, "The String-to-String Correction Problem," J. ACM, vol. 21, no. 1, Jan. 1974, pp. 168-173
49. G. Rogez, C. Orrite, and J. Martínez, "A Spatio-Temporal 2DModels Framework for Human Pose Recovery in Monocular Sequences," Pattern Recogn., vol. 41, no. 9, Sept. 2008, pp. 2926-2944
50. G. Rogez et al., "Randomized Trees for Human Pose Detection," IEEE CPVR, Anchorage, AK, USA, 2008, pp. 1-8
51. L. Sigal, A. Balan, and M.J. Black, "HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion," Int. J. Comput. Vis., vol. 87, no. 1-2, Mar. 2010, pp. 4-27