2D action recognition serves 3D human pose estimation

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

Volumn 6313 LNCS, Issue PART 3, 2010, Pages 425-438

  Gall, Juergen ^a   Yao, Angela ^a   Van Gool, Luc ^a,b  

^a ETH ZURICH   (Switzerland)

^b UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

EMBEDDINGS;

3D HUMAN POSE ESTIMATION; ACTION RECOGNITION; ACTION RECOGNITION SYSTEMS; JOINT OPTIMIZATION; LOW-DIMENSIONAL MANIFOLDS; OPTIMIZATION ALGORITHMS; PRACTICAL SOLUTIONS; PRIOR DISTRIBUTION;

COMPUTER VISION;

EID: 78149311511     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15558-1_31     Document Type: Conference Paper

References (33)

1. Agarwal, A., Triggs, B.: Recovering 3d human pose from monocular images. TPAMI 28(1), 44-58 (2006) (Pubitemid 46395303)
2. Baak, A., Rosenhahn, B., Müller, M., Seidel, H.P.: Stabilizing motion tracking using retrieved motion priors. In: ICCV (2009)
3. Bo, L., Sminchisescu, C.: Twin gaussian processes for structured prediction. IJCV 87, 28-52 (2010)
4. Chen, J., Kim, M., Wang, Y., Ji, Q.: Switching gaussian process dynamic models for simultaneous composite motion tracking and recognition. In: CVPR (2009)
5. Deutscher, J., Reid, I.: Articulated body motion capture by stochastic search. IJCV 61(2), 185-205 (2005)
6. Gall, J., Rosenhahn, B., Brox, T., Seidel, H.P.: Optimization and filtering for human motion capture - a multi-layer framework. IJCV 87, 75-92 (2010)
7. Gall, J., Rosenhahn, B., Seidel, H.P.: An Introduction to Interacting Simulated Annealing. In: Human Motion: Understanding, Modelling, Capture and Animation, pp. 319-343. Springer, Heidelberg (2008)
8. Grauman, K., Shakhnarovich, G., Darrell, T.: Inferring 3d structure with a statistical image-based shape model. In: ICCV, pp. 641-648 (2003)
9. Kittler, J., Society, I.C., Hatef, M., Duin, R.P.W., Matas, J.: On combining classi- fiers. TPAMI 20, 226-239 (1998)
10. Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. ACM Trans. Graph. 21(3), 473-482 (2002)
11. Lee, C.S., Elgammal, A.: Coupled visual and kinematic manifold models for tracking. IJCV 87, 118-139 (2010)
12. Li, R., Tian, T.P., Sclaroff, S., Yang, M.H.: 3d human motion tracking with a coordinated mixture of factor analyzers. IJCV 87, 170-190 (2010)
13. Lv, F., Nevatia, R.: Single view human action recognition using key pose matching and viterbi path searching. In: CVPR (2007)
14. Moeslund, T., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. CVIU 104(2), 90-126 (2006) (Pubitemid 44573873)
15. Moon, K., Pavlovic, V.: Impact of dynamics on subspace embedding and tracking of sequences. In: CVPR, pp. 198-205 (2006)
16. Moral, P.D.: Feynman-Kac Formulae. Genealogical and Interacting Particle Systems with Applications. Springer, New York (2004)
17. Pingkun Yan, S.M.K., Shah, M.: Learning 4d action feature models for arbitrary view action recognition. In: CVPR (2008)
18. Poppe, R.: A survey on vision-based human action recognition. Image and Vision Computing (2010)
19. Rasmussen, C.E., Williams, C.K.I.: Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). MIT Press, Cambridge (2005)
20. Shaheen, M., Gall, J., Strzodka, R., van Gool, L., Seidel, H.P.: A comparison of 3d model-based tracking approaches for human motion capture in uncontrolled environments. In: IEEE Workshop on Applications of Computer Vision (2009)
21. Sheikh, Y., Sheikh, M., Shah, M.: Exploring the space of a human action. In: ICCV (2005)
22. Sidenbladh, H., Black, M., Sigal, L.: Implicit probabilistic models of human motion for synthesis and tracking. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 784-800. Springer, Heidelberg (2002)
23. Sigal, L., Balan, A., Black, M.: Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion. IJCV 87, 4-27 (2010)
24. Sminchisescu, C., Kanaujia, A., Metaxas, D.: Bme: Discriminative density propagation for visual tracking. TPAMI 29(11), 2030-2044 (2007) (Pubitemid 47423794)
25. Souvenir, R., Babbs, J.: Learning the viewpoint manifold for action recognition. In: CVPR (2008)
26. Tenenbaum, J.B., de Silva, V., Langford, J.C.: A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science 290(5500), 2319-2323 (2000)
27. Tenorth, M., Bandouch, J., Beetz, M.: The TUM kitchen data set of everyday manipulation activities for motion tracking and action recognition. In: IEEE Workshop on THEMIS (2009)
28. Ukita, N., Hirai, M., Kidode, M.: Complex volume and pose tracking with probabilistic dynamical model and visual hull constraint. In: ICCV (2009)
29. Urtasun, R., Fleet, D., Fua, P.: 3d people tracking with gaussian process dynamical models. In: CVPR, pp. 238-245 (2006)
30. Urtasun, R., Fua, P.: 3d human body tracking using deterministic temporal motion models. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3023, pp. 92- 106. Springer, Heidelberg (2004)
31. Weinland, D., Boyer, E., Ronfard, R.: Action recognition from arbitrary views using 3d exemplars. In: ICCV, pp. 1-7 (2007)
32. Weinland, D., Ronfard, R., Boyer, E.: Free viewpoint action recognition using motion history volumes. CVIU 104(2-3), 249-257 (2006) (Pubitemid 44573869)
33. Yao, A., Gall, J., van Gool, L.: A hough transform-based voting framework for action recognition. In: CVPR (2010)