Realtime multi-person 2D pose estimation using part affinity fields

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 1302-1310

  Cao, Zhe ^a   Simon, Tomas ^a   Wei, Shih En ^a   Sheikh, Yaser ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTER VISION;

GLOBAL CONTEXT; MULTIPLE PEOPLE; NON-PARAMETRIC; NUMBER OF PEOPLES; POSE ESTIMATION; REAL TIME PERFORMANCE; SEQUENTIAL PREDICTION; STATE OF THE ART;

PATTERN RECOGNITION;

EID: 85042428134     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.143     Document Type: Conference Paper

References (33)

1. MSCOCO keypoint evaluation metric. http://mscoco.org/dataset/#keypoints-eval.
2. M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele. 2D human pose estimation: new benchmark and state of the art analysis. In CVPR, 2014.
3. M. Andriluka, S. Roth, and B. Schiele. Pictorial structures revisited: people detection and articulated pose estimation. In CVPR, 2009.
4. M. Andriluka, S. Roth, and B. Schiele. Monocular 3D pose estimation and tracking by detection. In CVPR, 2010.
5. V. Belagiannis and A. Zisserman. Recurrent human pose estimation. In 12th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), 2017.
6. A. Bulat and G. Tzimiropoulos. Human pose estimation via convolutional part heatmap regression. In ECCV, 2016.
7. X. Chen and A. Yuille. Articulated pose estimation by a graphical model with image dependent pairwise relations. In NIPS, 2014.
8. P. F. Felzenszwalb and D. P. Huttenlocher. Pictorial structures for object recognition. In IJCV, 2005.
9. G. Gkioxari, B. Hariharan, R. Girshick, and J. Malik. Using k-poselets for detecting people and localizing their keypoints. In CVPR, 2014.
10. K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. In CVPR, 2016.
11. E. Insafutdinov, L. Pishchulin, B. Andres, M. Andriluka, and B. Schiele. Deepercut: A deeper, stronger, and faster multiperson pose estimation model. In ECCV, 2016.
12. U. Iqbal and J. Gall. Multi-person pose estimation with local joint-to-person associations. In ECCV Workshops, Crowd Understanding, 2016.
13. S. Johnson and M. Everingham. Clustered pose and nonlinear appearance models for human pose estimation. In BMVC, 2010.
14. H. W. Kuhn. The hungarian method for the assignment problem. In Naval research logistics quarterly. Wiley Online Library, 1955.
15. T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick. Microsoft COCO: common objects in context. In ECCV, 2014.
16. W. Liu, D. Anguelov, D. Erhan, C. Szegedy, and S. Reed. Ssd: Single shot multibox detector. In ECCV, 2016.
17. A. Newell, K. Yang, and J. Deng. Stacked hourglass networks for human pose estimation. In ECCV, 2016.
18. W. Ouyang, X. Chu, and X. Wang. Multi-source deep learning for human pose estimation. In CVPR, 2014.
19. G. Papandreou, T. Zhu, N. Kanazawa, A. Toshev, J. Tompson, C. Bregler, and K. Murphy. Towards accurate multi-person pose estimation in the wild. arXiv preprint arXiv: 1701.01779, 2017.
20. T. Pfister, J. Charles, and A. Zisserman. Flowing convnets for human pose estimation in videos. In ICCV, 2015.
21. L. Pishchulin, M. Andriluka, P. Gehler, and B. Schiele. Poselet conditioned pictorial structures. In CVPR, 2013.
22. L. Pishchulin, E. Insafutdinov, S. Tang, B. Andres, M. Andriluka, P. Gehler, and B. Schiele. Deepcut: Joint subset partition and labeling for multi person pose estimation. In CVPR, 2016.
23. L. Pishchulin, A. Jain, M. Andriluka, T. Thormählen, and B. Schiele. Articulated people detection and pose estimation: Reshaping the future. In CVPR, 2012.
24. V. Ramakrishna, D. Munoz, M. Hebert, J. A. Bagnell, and Y. Sheikh. Pose machines: Articulated pose estimation via inference machines. In ECCV, 2014.
25. D. Ramanan, D. A. Forsyth, and A. Zisserman. Strike a Pose: Tracking people by finding stylized poses. In CVPR, 2005.
26. K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. In ICLR, 2015.
27. M. Sun and S. Savarese. Articulated part-based model for joint object detection and pose estimation. In ICCV, 2011.
28. J. Tompson, R. Goroshin, A. Jain, Y. LeCun, and C. Bregler. Efficient object localization using convolutional networks. In CVPR, 2015.
29. J. J. Tompson, A. Jain, Y. LeCun, and C. Bregler. Joint training of a convolutional network and a graphical model for human pose estimation. In NIPS, 2014.
30. A. Toshev and C. Szegedy. Deeppose: Human pose estimation via deep neural networks. In CVPR, 2014.
31. S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh. Convolutional pose machines. In CVPR, 2016.
32. D. B. West et al. Introduction to graph theory, Volume 2. Prentice hall Upper Saddle River, 2001.
33. Y. Yang and D. Ramanan. Articulated human detection with flexible mixtures of parts. In TPAMI, 2013.