Exploring the spatial hierarchy of mixture models for human pose estimation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7576 LNCS, Issue PART 5, 2012, Pages 256-269

  Tian, Yuandong ^a   Zitnick, C Lawrence ^b   Narasimhan, Srinivasa G ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; DEFORMABLE MODELS; EXACT INFERENCE; EXPONENTIAL NUMBERS; HIERARCHICAL MODEL; HIERARCHICAL STRUCTURES; HIGH-ORDER; HUMAN POSE ESTIMATIONS; LATENT NODES; MIXTURE MODEL; NEAREST NEIGHBORS; POSE SPACE; SPATIAL HIERARCHY; SPATIAL MODELS; SPATIAL PRIORS; SPATIAL RELATIONSHIPS; STATE-OF-ART PERFORMANCE;

HIERARCHICAL SYSTEMS; MIXTURES;

COMPUTER VISION;

EID: 84867878385     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33715-4_19     Document Type: Conference Paper

References (18)

1. Andriluka, M., Roth, S., Schiele, B.: Pictorial structures revisited: People detection and articulated pose estimation. In: Computer Vision and Pattern Recognition, pp. 1014-1021. IEEE (2009)
2. Bergtholdt, M., Kappes, J., Schmidt, S., Schnörr, C.: A study of parts-based object class detection using complete graphs. International Journal of Computer Vision 87(1), 93-117 (2010)
3. Bourdev, L., Malik, J.: Poselets: Body part detectors trained using 3d human pose annotations. In: International Conference on Computer Vision, ICCV (2009)
4. Eichner, M., Ferrari, V.: Better appearance models for pictorial structures. In: BMVC (2009)
5. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient matching of pictorial structures. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 66-73. IEEE (2000)
6. Ferrari, V., Marin-Jimenez, M., Zisserman, A.: Progressive search space reduction for human pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1-8. IEEE (2008)
7. Fischler, M.A., Elschlager, R.A.: The representation and matching of pictorial structures. IEEE Transactions on Computers 100(1), 67-92 (1973)
8. Johnson, S., Everingham, M.: Clustered pose and nonlinear appearance models for human pose estimation. In: BMVC (2010)
9. Johnson, S., Everingham, M.: Learning effective human pose estimation from inaccurate annotation. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1465-1472. IEEE (2011)
10. Lan, X., Huttenlocher, D.P.: Beyond trees: Common-factor models for 2d human pose recovery. In: Tenth IEEE International Conference on Computer Vision, ICCV 2005, vol. 1, pp. 470-477. IEEE (2005)
11. Marr, D., Nishihara, H.K.: Representation and recognition of the spatial organization of three-dimensional shapes. Proceedings of the Royal Society of London. Series B. Biological Sciences 200(1140), 269-294 (1978)
12. Ramanan, D.: Learning to parse images of articulated bodies. In: NIPS, vol. 19, p. 1129 (2007)
13. Sun, M., Savarese, S.: Articulated part-based model for joint object detection and pose estimation. In: ICCV (2011)
14. Tian, T.P., Sclaroff, S.: Fast globally optimal 2d human detection with loopy graph models. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 81-88. IEEE (2010)
15. Tran, D., Forsyth, D.: Improved Human Parsing with a Full Relational Model. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 227-240. Springer, Heidelberg (2010)
16. Wang, Y., Tran, D., Liao, Z.: Learning hierarchical poselets for human parsing. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1705-1712. IEEE (2011)
17. Yang, Y., Ramanan, D.: Articulated pose estimation with flexible mixtures-ofparts. In: Computer Vision and Pattern Recognition (CVPR), pp. 1385-1392. IEEE (2011)
18. Zhu, L.L., Chen, Y., Yuille, A., Freeman,W.: Latent hierarchical structural learning for object detection. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1062-1069. IEEE (2010)