Recognizing human actions using key poses

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2010, Pages 1727-1730

  Baysal, Sermetcan ^a   Kurt, Mehmet Can ^a   Duygulu, Pinar ^a  

^a BILKENT UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

A-FRAMES; ACTION SEQUENCES; COMPLEX ACTIONS; DATA SETS; HUMAN ACTIONS; HUMAN-ACTION RECOGNITION; KEY POSE; MATCHING SCHEME; POSE INFORMATION; SIMPLE METHOD; TEMPORAL INFORMATION;

GESTURE RECOGNITION;

EID: 78149486639     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2010.427     Document Type: Conference Paper

References (17)

1. M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Basri. Actions as space-time shapes. International Conference on Computer Vision (ICCV), 2005.
2. P. Dollar, V. Rabaud, G. Cottrell, and S. Belongie. Behavior recognition via sparse spatio-temporal features. VS-PETS, 2005.
3. A. A. Efros, A. C. Berg, G. Mori, and J. Malik. Recognizing action at a distance. International Conference on Computer Vision (ICCV), 2003.
4. A. Fathi and G. Mori. Action recognition by learning mid-level motion features. Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
5. V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid. Groups of adjacent contour segments for object detection. IEEE Trans. Pattern Anal. Mach. Intel l., 30(1):36-51, 2008.
6. N. Ikizler, R. G. Cinbis and P. Duygulu. Human action recognition with line and flow histograms. International Conference on Pattern Recognition (ICPR), 2008.
7. N. Ikizler and P. Duygulu. Histogram of oriented rectangles: a new pose descriptor of human action recognition. Image and Vision Computing, 27(10):1515-1526, 2009.
8. Y. Ke, R. Sukthankar, and M. Hebert. Spatio-temporal shape and flow correlation for action recognition. Visual Surveillance Workshop, 2007.
9. Z. Lin, Z. Jiang, and L. S. Davis. Recognizing actions by shape-motion prototype trees. International Conference on Computer Vision (ICCV), 2009.
10. J. Liu, J. Luo, and M. Shah. Recognizing realistic actions from videos "in the wild". Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
11. M. Maire, P. Arbelaez, C. Fowlkes, J. Malik. Using contours to detect and localize junctions in natural images. Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
12. J. C. Niebles, H. Wang, and L. Fei-Fei. Unsupervised learning of human action categories using spatial-temporal words. Int'l J. Computer Vision, 79(3):299-318, 2008.
13. S. Nowozin, G. Bakir, and K. Tsuda. Discriminative subsequence mining for action classification. International Conference on Computer Vision (ICCV), 2007.
14. K. Schindler and L. V. Gool. Action snippets: how many frames does human action recognition require? Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
15. C. Schuldt, I. Laptev, and B. Caputo. Recognizing human actions: a local SVM approach. International Conference on Pattern Recognition (ICPR), 2004.
16. C. Thurau and V. Hlavac. Pose primitive based human action recognition in videos or still images. Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
17. Y. Wang, P. Sabzmeydani, and G. Mori. Semi-latent Dirichlet allocation: a hierarchical model for human action recognition. International Conference on Computer Vision (ICCV), Workshop on Human Motion, 2007.