Bio-inspired predictive orientation decomposition of skeleton trajectories for real-time human activity prediction

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2015-June, Issue June, 2015, Pages 3053-3060

  Zhang, Hao ^a   Parker, Lynne E ^b  

^a Department of Metallurgical and Materials Engineering   (United States)

^b University of Tennessee   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL ROBOTS; ASSISTED LIVING; BIOMIMETICS; CLASSIFICATION (OF INFORMATION); FORECASTING; ROBOTICS; TRAJECTORIES;

ACTIVITY CLASSIFICATIONS; ACTIVITY PREDICTIONS; BENCHMARK DATASETS; BIOLOGICAL RESEARCH; HUMAN CENTERED ROBOTICS; INCOMPLETE OBSERVATION; PREDICTIVE CAPABILITIES; SPATIOTEMPORAL INFORMATION;

MUSCULOSKELETAL SYSTEM;

EID: 84938276849     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2015.7139618     Document Type: Conference Paper

References (31)

1. J. Aggarwal and L. Xia, "Human activity recognition from 3d data: A review," Pattern Recognition Letters, vol. 48, no. 0, pp. 70-80, 2014
2. G. Chen, M. Giuliani, D. Clarke, A. Gaschler, and A. Knoll, "Action recognition using ensemble weighted multi-instance learning," in IEEE International Conference on Robotics and Automation, 2014
3. A. Pieropan, G. Salvi, K. Pauwels, and H. Kjellstrom, "Audiovisual classification and detection of human manipulation actions," in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014
4. H. Zhang and L. Parker, "4-dimensional local spatio-temporal features for human activity recognition," in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011
5. H. Zhang, C. M. Reardon, and L. E. Parker, "Real-time multiple human perception with color-depth cameras on a mobile robot," IEEE Trans. Cybernetics, vol. 43, no. 5, pp. 1429-1441, 2013
6. J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake, "Real-time human pose recognition in parts from single depth images," in IEEE Conference on Computer Vision and Pattern Recognition, 2011
7. M. Müller, T. Röder, M. Clausen, B. Eberhardt, B. Krüger, and A. Weber, "Documentation mocap database hdm05," tech. rep., Universität Bonn, Jun. 2007
8. J. Sung, C. Ponce, B. Selman, and A. Saxena, "Unstructured human activity detection from rgbd images," in IEEE International Conference on Robotics and Automation, 2012
9. J. Wang, Z. Liu, Y. Wu, and J. Yuan, "Mining actionlet ensemble for action recognition with depth cameras," in IEEE Conference on Computer Vision and Pattern Recognition, 2012
10. M. Zanfir, M. Leordeanu, and C. Sminchisescu, "The moving pose: An efficient 3D kinematics descriptor for low-latency action recognition and detection," in IEEE International Conference on Computer Vision, 2013
11. H. Rahmani, A. Mahmood, A. Mian, and D. Huynh, "Real time action recognition using histograms of depth gradients and random decision forests," in IEEE Winter Conference on Applications of Computer Vision, 2014
12. M. A. Gowayyed, M. Torki, M. E. Hussein, and M. El-Saban, "Histogram of oriented displacements (HOD): Describing trajectories of human joints for action recognition," in International Joint Conference on Artificial Intelligence, 2013
13. M. E. Hussein, M. Torki, M. A. Gowayyed, and M. El-Saban, "Human action recognition using a temporal hierarchy of covariance descriptors on 3D joint locations," in International Joint Conference on Artificial Intelligence, 2013
14. H. Gray, Anatomy of the Human Body. Lea & Febiger, 1973
15. C. Yokochi and J. W. Rohen, Color Atlas of Anatomy: A Photographic Study of the Human Body. Lippincott Williams & Wilkins, 2006
16. A. Mori, S. Uchida, R. Kurazume, R.-I. Taniguchi, T. Hasegawa, and H. Sakoe, "Early recognition and prediction of gestures," in International Conference on Pattern Recognition, 2006
17. M. Hoai and F. De la Torre, "Max-margin early event detectors," International Journal of Computer Vision, vol. 107, no. 2, pp. 191-202, 2014
18. C. Ellis, S. Z. Masood, M. F. Tappen, J. J. Laviola, Jr., and R. Sukthankar, "Exploring the trade-off between accuracy and observational latency in action recognition," International Journal of Computer Vision, vol. 101, pp. 420-436, Feb. 2013
19. J. Hoare and L. Parker, "Using on-line conditional random fields to determine human intent for peer-to-peer human robot teaming," in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010
20. M. S. Ryoo, "Human activity prediction: Early recognition of ongoing activities from streaming videos," in International Conference on Computer Vision, pp. 1036-1043, 2011
21. G. Yu, J. Yuan, and Z. Liu, "Predicting human activities using spatio-temporal structure of interest points," in ACM International Conference on Multimedia, 2012
22. M. McGinnis, Bioregionalism: The Tug and Pull of Place. Routledge, 1999
23. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in IEEE Conference on Computer Vision and Pattern Recognition, 2001
24. G. Einicke and L. White, "Robust extended Kalman filtering," IEEE Trans. Signal Processing, vol. 47, pp. 2596-2599, Sept. 1999
25. C.-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines," ACM Trans. Intelligent Systems and Technology, vol. 2, pp. 27:1-27:27, 2011
26. A. Vedaldi and A. Zisserman, "Efficient additive kernels via explicit feature maps," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 3, pp. 480-492, 2012
27. L. Xia and J. K. Aggarwal, "Spatio-temporal depth cuboid similarity feature for activity recognition using depth camera," in IEEE Conference on Computer Vision and Pattern Recognition, 2013
28. L. Seidenari, V. Varano, S. Berretti, A. Del Bimbo, and P. Pala, "Recognizing actions from depth cameras as weakly aligned multi-part bag-of-poses," in IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2013
29. F. Ofli, R. Chaudhry, G. Kurillo, R. Vidal, and R. Bajcsy, "Sequence of the most informative joints (smij): A new representation for human skeletal action recognition," Journal of Visual Communication and Image Representation, vol. 25, pp. 24-38, Jan. 2014
30. Q. Liu and X. Cao, "Action recognition using subtensor constraint," in European Conference on Computer Vision, 2012
31. A. López-Mendez, J. Gall, J. R. Casas, and L. J. V. Gool, "Metric learning from poses for temporal clustering of human motion," in British Machine Vision Conference, 2012.