Human action segmentation with hierarchical supervoxel consistency

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 07-12-June-2015, Issue , 2015, Pages 3762-3771

  Lu, Jiasen ^a   Xu, Ran ^a   Corso, Jason J ^b  

^a State University of New York   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; MOTION ANALYSIS; MOTION ESTIMATION;

ACTION CLASSIFICATIONS; ACTION SEGMENTATION; AUTOMATIC SEGMENTATIONS; DETECTION AND LOCALIZATION; HIGHER ORDER POTENTIALS; HUMAN ACTION SEGMENTATIONS; HUMAN SEGMENTATION; SINGLE-LAYER MODELS;

PATTERN RECOGNITION;

EID: 84959217808     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7299000     Document Type: Conference Paper

References (39)

1. Y. Boykov, O. Veksler, and R. Zabih. Fast Approximate Energy Minimization via Graph Cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11):1222-1239, 2001
2. T. Brox and J. Malik. Object segmentation by long term analysis of point trajectories. In European Conference on Computer Vision. 2010
3. T. Brox and J. Malik. Large displacement optical flow: Descriptor matching in variational motion estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(3):500-513, 2011
4. D. Burschka, J. J. Corso, M. Dewan, W. Lau, M. Li, H. Lin, P. Marayong, N. Ramey, G. D. Hager, B. Hoffman, D. Larkin, and C. Hasser. Navigating Inner Space: 3-D Assistance for Minimally Invasive Surgery. Robotics and Au-tonomous System, 2005
5. W. Chen, C. Xiong, R. Xu, and J. Corso. Actionness ranking with lattice conditional ordinal random fields. In IEEE Con-ference on Computer Vision and Pattern Recognition, 2014
6. K. G. Derpanis, M. Sizintsev, K. Cannons, and R. P. Wildes. Efficient action spotting based on a spacetime oriented structure representation. In IEEE Conference on Computer Vision and Pattern Recognition, 2010
7. P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained partbased models. IEEE transactions on pattern analysis and machine intelligence, 32(9):1627-45, 2010
8. L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri. Actions as space-time shapes. IEEE Transactions on Pat-tern Analysis and Machine Intelligence, 29(12):2247-2253, 2007
9. M. Grundmann, V. Kwatra, M. Han, and I. Essa. Efficient hierarchical graph-based video segmentation. In IEEE Con-ference on Computer Vision and Pattern Recognition, 2010
10. J. Guo, Z. Li, L.-F. Cheong, and S. Zhou. Video cosegmentation for meaningful action extraction. In IEEE In-ternational Conference on Computer Vision, Dec 2013
11. A. Gupta, A. Kembhavi, and L. S. Davis. Observing humanobject interactions: Using spatial and functional compatibility for recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 2009
12. P. Huber. Robust statistics. Wiley, New York, 1981
13. M. Jain, H. Jegou, and P. Bouthemy. Better exploiting motion for better action recognition. In IEEE Conference on Computer Vision and Pattern Recognition, 2013
14. M. Jain, J. C. van Gemert, H. Jégou, P. Bouthemy, and C. G. M. Snoek. Action localization by tubelets from motion. In IEEE Conference on Computer Vision and Pattern Recognition, 2014
15. S. Jain and K. Grauman. Supervoxel-consistent foreground propagation in video. In European Conference on Computer Vision. 2014
16. H. Jhuang, J. Gall, S. Zuffi, C. Schmid, and M. J. Black. Towards understanding action recognition. In IEEE Interna-tional Conference on Computer Vision, Dec. 2013
17. A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei. Large-scale video classification with convolutional neural networks. In IEEE Conference on Computer Vision and Pattern Recognition, 2014
18. Y. Ke, R. Sukthankar, and M. Hebert. Spatio-temporal shape and flow correlation for action recognition. In IEEE Interna-tional Conference on Computer Vision, 2007
19. P. Kohli, P. H. Torr, et al. Robust higher order potentials for enforcing label consistency. International Journal of Com-puter Vision, 82(3):302-324, 2009
20. H. Kuehne, H. Jhuang, E. Garrote, T. Poggio, and T. Serre. Hmdb: A large video database for human motion recognition. In IEEE International Conference on Computer Vision, 2011
21. T. Lan, Y. Wang, and G. Mori. Discriminative figure-centric models for joint action localization and recognition. In IEEE International Conference on Computer Vision, Nov 2011
22. T. Lan, Y. Wang, W. Yang, and G. Mori. Beyond actions: Discriminative models for contextual group activities. In Proceedings of Advance in Neutral Information Processing, 2010
23. J. Leonard, J. How, S. Teller, M. Berger, S. Campbell, G. Fiore, L. Fletcher, E. Frazzoli, A. Huang, and S. Karaman. A perception-driven autonomous urban vehicle. Journal of Field Robotics, 25(10):727-774, 2008
24. S. Ma, J. Zhang, N. Ikizler-Cinbis, and S. Sclaroff. Action recognition and localization by hierarchical space-time segments. In IEEE International Conference on Computer Vi-sion, 2013
25. J.-M. Odobez and P. Bouthemy. Robust multiresolution estimation of parametric motion models. In Journal of Visual Communication and Image Representation, 1995
26. D. Oneata, J. Revaud, J. Verbeek, and C. Schmid. Spatiotemporal object detection proposals. In European Confer-ence on Computer Vision, 2014
27. M. D. Rodriguez, J. Ahmed, and M. Shah. Action mach: A spatio-temporal maximum average correlation height filter for action recognition. In IEEE Conference on Computer Vision and Pattern Recognition, 2008
28. S. Sadanand and J. J. Corso. Action bank: A high-level representation of activity in video. In IEEE Conference on Com-puter Vision and Pattern Recognition, 2012
29. Y. Sheikh, O. Javed, and T. Kanade. Background subtraction for freely moving cameras. In IEEE International Confer-ence on Computer Vision, 2009
30. K. Soomro, A. R. Zamir, and M. Shah. A dataset of 101 human action classes from videos in the wild. Technical report, University of Central Florida, Center for Research in Computer Vision, 2012
31. Y. Tian, R. Sukthankar, and M. Shah. Spatiotemporal deformable part models for action detection. In IEEE Confer-ence on Computer Vision and Pattern Recognition, 2013
32. C. Wang, Y. Wang, and A. L. Yuille. An approach to posebased action recognition. In IEEE Conference on Computer Vision and Pattern Recognition, 2013
33. H. Wang, A. Kläser, C. Schmid, and C.-L. Liu. Action Recognition by Dense Trajectories. In IEEE Conference on Computer Vision and Pattern Recognition, 2011
34. H. Wang and C. Schmid. Action recognition with improved trajectories. In IEEE International Conference on Computer Vision, 2013
35. L. Wang, Y. Qiao, and X. Tang. Video action detection with relational dynamic-poselets. In European Conference on Computer Vision, 2014
36. C. Xu and J. J. Corso. Evaluation of super-voxel methods for early video processing. In IEEE Conference on Computer Vision and Pattern Recognition, 2012
37. C. Xu, S. Whitt, and J. Corso. Flattening supervoxel hierarchies by the uniform entropy slice. In IEEE Conference on Computer Vision and Pattern Recognition, Dec 2013
38. C. Xu, C. Xiong, and J. J. Corso. Streaming hierarchical video segmentation. In Proceedings of European Conference on Computer Vision, 2012
39. W. Zhang, M. Zhu, and K. G. Derpanis. From actemes to action: A strongly-supervised representation for detailed action understanding. In IEEE International Conference on Computer Vision, 2013.