Clustered pose and nonlinear appearance models for human pose estimation

British Machine Vision Conference, BMVC 2010 - Proceedings

Volumn , Issue , 2010, Pages

  Johnson, Sam ^a   Everingham, Mark ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION;

ANNOTATED DATABASE; APPEARANCE MODELS; COMPUTATIONAL EXPENSE; DISCRIMINATIVE CLASSIFIERS; HUMAN POSE ESTIMATIONS; IMAGING CONDITIONS; PICTORIAL STRUCTURES; STATE-OF-THE-ART METHODS;

MOTION ESTIMATION;

EID: 84898472539     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.24.12     Document Type: Conference Paper

References (24)

1. M. Andriluka, S. Roth, and B. Schiele. Pictorial structures revisited: People detection and articulated pose estimation. In Proc. CVPR, 2009.
2. C. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.
3. P. Buehler, M. Everingham, D. Huttenlocher, and A. Zisserman. Long term arm and hand tracking for continuous sign language TV broadcasts. In Proc. BMVC, 2008.
4. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Proc. CVPR, 2005.
5. J. Deutscher, A. Blake, and I. Reid. Articulated body motion capture by annealed particle filtering. In Proc. CVPR, 2000.
6. M. Eichner and V. Ferrari. Better appearance models for pictorial structures. In Proc. BMVC, 2009.
7. P. Felzenszwalb and D. Huttenlocher. Pictorial structures for object recognition. IJCV, 61(1), 2005.
8. P. Felzenszwalb, D. McAllester, and D. Ramanan. A discriminatively trained, multi-scale, deformable part model. In Proc. CVPR, 2008.
9. V. Ferrari, M. Marin-Jimenez, and A. Zisserman. Progressive search space reduction for human pose estimation. In Proc. CVPR, 2008.
10. D. Hogg. Model-based vision: A program to see a walking person. IVC, 1(1), 1983.
11. S. Ioffe and D. Forsyth. Mixtures of trees for object recognition. In Proc. CVPR, 2001.
12. S. Johnson and M. Everingham. Combining discriminative appearance and segmentation cues for articulated human pose estimation. In Proc. MLVMA, 2009.
13. M. Kumar, A. Zisserman, and P. Torr. Efficient discriminative learning of parts-based models. In Proc. ICCV, 2009.
14. M. Lee and I. Cohen. Human upper body pose estimation in static images. In Proc. ECCV, 2004.
15. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. PAMI, 27(10), 2005.
16. D. Ramanan. Learning to parse images of articulated bodies. In Proc. NIPS, 2006.
17. D. Ramanan and C. Sminchisescu. Training deformable models for localization. In Proc. CVPR, 2006.
18. D. Ramanan, D. Forsyth, and A. Zisserman. Strike a pose: tracking people by finding stylized poses. In Proc. CVPR, 2005.
19. S. Romdhani, P. Torr, B. Schölkopf, and A. Blake. Efficient face detection by a cascaded reduced support vector expansion. Proceedings of the Royal Society, 460(2501), 2004.
20. H. Sidenbladh and M. Black. Learning the statistics of people in images and video. IJCV, 2003.
21. L. Sigal, S. Bhatia, S. Roth, M. Black, and M. Isard. Tracking loose-limbed people. In Proc. CVPR, 2004.
22. P. Viola and M. Jones. Robust real-time object detection. IJCV, 2001.
23. Y. Wang and G. Mori. Multiple tree models for occlusion and spatial constraints in human pose estimation. In Proc. ECCV, 2008.
24. L. Xiangyang and D. Huttenlocher. Beyond trees: Common-factor models for 2d human pose recovery. In Proc. ICCV, 2005.