Modeling and recognition of actions through motor primitives

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2008, Pages 1704-1709

  Martínez, David ^a   Kragic, Danica ^a  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

INDUSTRIAL ENGINEERING; LEARNING SYSTEMS; MARKOV PROCESSES; ROBOTICS; ROBOTS; SUPPORT VECTOR MACHINES;

COMPLEX ACTIONS; INTERNATIONAL CONFERENCES; OBJECT MANIPULATIONS;

HIDDEN MARKOV MODELS;

EID: 51649098561     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2008.4543446     Document Type: Conference Paper

References (14)

1. M. Mataric, "Sensory-motor primitives as a basis for imitation: Linking perception to action and biology to robotics," 2000.
2. D. Newton et al, "The objective basis of behavior unit," Journal of Personality and Social Pshychology, vol. 35, no. 12, pp. 847-862, 1977.
3. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines. Cambridge, UK: Cambridge University Press, 2000.
4. L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proceedings of the IEEE, vol. 77, no. 2, pp. 257-286, 1989.
5. J. Lafferty, A. McCallum, and F. Pereira, "Conditional random fields: Probabilistic models for segmenting and labeling sequence data," in Proc. 18th International Conf. on Machine Learning, pp. 282-289, Morgan Kaufmann, San Francisco, CA, 2001.
6. T. B. Moeslund, A. Hilton, and V. Krüger, "A survey of advances in vision-based human motion capture and analysis," Comput. Vis. Image Underst., vol. 104, no. 2, pp. 90-126, 2006.
7. J. Sullivan and S. Carlsson, "Recognizing and tracking human action," in European Conference on Computer Vision, 2002.
8. C. Sminchisescu, A. Kanaujia, and D. Metaxas, "Conditional models for contextual human motion recognition," Computer Vision and Image Understanding, vol. 104, no. 2-3, 2005.
9. S. E. Golowich and D. X. Sun, "A support vector/hidden Markov model approach to phoneme recognition," in ASA Proceedings of the Statistical Computing Section, pp. 125-130, 1998.
10. H. Shimodaira, K. Noma, M. Nakai, and S. Sagayama, "Dynamic time-alignment kernel in support vector machine," in Advances in Neural Information Processing Systems, pp. 921-928, 2001.
11. M. Bartlett, G. Littlewort, B. Braathen, T. Sejnowski, and J. Movellan, "A prototype for automatic recognition of spontaneous facial actions," in Advances in Neural Information Processing Systems, NIPS 2003, pp. 1271-1278, 2002.
12. D. Surendran and G.-A. Levow, "Dialog act tagging with support vector machines and hidden Markov models," in Interspeech 2006 - ICSLP, (Pittsburgh, PA, USA), 2006.
13. V. Kyrki, I. Serrano, D. Kragic, and J.-O. Eklundh, "Action recognition and understanding using motor primitives," in In RO-MAN'07: The 16th IEEE International Symposium on Robot and Human Interactive Communication, Jeju Island, Korea, 2007.
14. S. Needleman and C. Wunsch, "A general method applicable to the search for similarity in the amino acid sequences of two proteins," Journal of Molecular Biology, vol. 48, pp. 443-453, 1970.