Gaussian mixture based HMM for human daily activity recognition using 3D skeleton features

Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013

Volumn , Issue , 2013, Pages 567-572

  Piyathilaka, Lasitha ^a   Kodagoda, Sarath ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC DETECTION; DAILY ACTIVITY; GAUSSIAN MIXTURES; HUMAN ACTIVITIES; HUMAN-ACTIVITY DETECTION; MICROSOFT KINECT; RGB-D SENSORS; SKELETON JOINTS;

COMPUTER VISION; HIDDEN MARKOV MODELS; MUSCULOSKELETAL SYSTEM;

INDUSTRIAL ELECTRONICS;

EID: 84881410216     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIEA.2013.6566433     Document Type: Conference Paper

References (17)

1. T. Theodoridis, A. Agapitos, H. Hu, and S. M. Lucas, "Ubiquitous robotics in physical human action recognition: A comparison between dynamic anns and gp. " in ICRA. IEEE, 2008, pp. 3064-3069.
2. Y. Demiris and A. Meltzoff, "The robot in the crib: A developmental analysis of imitation skills in infants and robots." Infant Child Dev, vol. 17, no. 1, pp. 43-53, 2008.
3. M. Lopes, F. S. Melo, and L. Montesano, "Affordance-based imitation learning in robots", in IEEE/RSJ International Conference on Intelligent Robots and Systems, USA, Nov. 2007, pp. 1015-1021.
4. S. Bang, M. Kim, S.-K. Song, and S.-J. Park, "Toward real time detection of the basic living activity in home using a wearable sensor and smart home sensors", Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2008, pp. 5200-5203, 2008.
5. E. M. Tapia, S. S. Intille, and K. Larson, "Activity Recognition in the Home Using Simple and Ubiquitous Sensors", Pervasive Computing, vol. 3001, pp. 158-175, 2004.
6. D. T. G. Huynh, "Human activity recognition with wearable sensors", Ph. D. dissertation, TU Darmstadt, September 2008. [Online]. Available: http://tuprints.ulb.tu-darmstadt.de/1132/
7. A. Gupta, P. Srinivasan, J. Shi, and L. S. Davis, "Understanding videos, constructing plots learning a visually grounded storyline model from annotated videos", 2009 IEEE Conference on Computer Vision and Pattern Recognition, vol. 21, no. 4, pp. 2012-2019, 2009.
8. J. Sung, C. Ponce, B. Selman, and A. Saxena, "Human activity detection from rgbd images." in Plan, Activity, and Intent Recognition, vol. WS-11-16. AAAI, 2011.
9. M. Brand, N. Oliver, and A. Pentland, "Coupled hidden Markov models for complex action recognition", Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 0, pp. 994-999, 1997.
10. F. Martinez-Contreras, C. Orrite-Urunuela, E. Herrero-Jaraba, H. Ragheb, and S. A. Velastin, "Recognizing Human Actions Using Silhouette-based HMM", 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 43-48, 2009.
11. A. V. Nefian, L. Liang, X. Pi, X. Liu, and K. Murphy, "Dynamic Bayesian Networks for Audio-Visual Speech Recognition", EURASIP Journal on Advances in Signal Processing, vol. 2002, no. 11, pp. 1274-1288, 2002.
12. A. V. Nefian, L. Liang, X. Pi, L. Xiaoxiang, C. Mao, and K. Murphy, "A coupled hmm for audio-visual speech recognition", in in International Conference on Acoustics, Speech and Signal Processing (CASSP?02, 2002, pp. 2013-2016.
13. K. Murphy, "Dynamic bayesian networks: Representation, inference and learning", Ph. D. dissertation, UC Berkeley, Computer Science Division, Jul. 2002.
14. K. P. Murphy, "The bayes net toolbox for matlab", Computing Science and Statistics, vol. 33, p. 2001, 2001.
15. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the em algorithm", JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B, vol. 39, no. 1, pp. 1-38, 1977.
16. J. A. Hartigan and M. A. Wong, "A K-means clustering algorithm", Applied Statistics, vol. 28, pp. 100-108, 1979.
17. L. Rabiner, "A tutorial on hidden markov models and selected applications in speech recognition", Proceedings of the IEEE, vol. 77, no. 2, pp. 257-286, Feb. 1989.